177 research outputs found

    Visual Gender Stereotypes (Advertisement, Social Media)

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    The depiction of gender is the focus of a growing number of content analyses in the fields of both mass media (e.g., Goffman, 1979; Grau & Zotos, 2016; Mitchell & McKinnon, 2019; Sink & Mastro, 2017; Ward & Grower, 2020) and social media (e.g., Baker & Walsh, 2018; Döring, 2019; Döring & Mohseni, 2019; Döring et al., 2016). Typically, the depiction of gender follows traditional gender roles and, hence, does not include at lot of individuality and diversity but sticks to established gender stereotypes (Collins, 2011). Gender steoreotypes are defined as beliefs about how men versus women are (descriptive beliefs) or should be (prescriptive beliefs). Relevant dimensions of gender stereotyping are occupations (e.g., the man as the hero, breadwinner, or executive; the woman as the mother, housewife, or subordinate), sexual and romantic behaviors (e.g., the man seeking sex; the woman seeking love), personality traits (e.g., the man being active, aggressive, rational, and instrumental; the woman being passive, affectionate, emotional, and social), or body types (e.g., the man being tall, muscular and older; the woman being petite, slim, and younger). Gender stereotypes in the media cover different dimensions of traditional masculinity and feminity and are represented textually and/or (audio-)visually. Typically, the occurrence and nature of gender stereotyping in different media is measured and changes over time are of particular interest (e.g., Bhatia & Bhatia, 2020; Maker & Childs, 2003).   Field of application/theoretical foundation: According to the Social Cognitive Theory (SCT; Bandura 1986, 2009), gender-stereotyped protagonists in the media can influence how media audiences perceive gender roles and to which degree they imitate them as role models. Cultivation theory (Gerbner & Gross, 1976; Kim & Lowry, 2005) predicts, that exposure to distorted media images of reality will shape the audiences’ worldviews. Repeated or constant exposure to gender stereotpyes in the media, according to cultivation theory, will influence the audiences’ perceptions of the roles of women and men in society. Against the background of human rights and gender equality, exaggerated gender stereotypes and the related subordination of women in the media are criticized (e.g. Döring et al., 2016; Goffman, 1979; Grau & Zotos, 2016). Often times, gender-related media content analyses support feminist claims about gender-based inequalities (Collins, 2011; Rudy et al., 2010). When criticizing gender steoreotypes in the media, it is important to realize, though, that media do not one-directionally influence public perception and opinion (mold theory) but also bi-directionally reflect existing social gender relations and societal attitudes (mirror theory). Last but not least, based on an understanding of stereotypes as cognitive shortcuts and simplifications (Windels, 2016) it needs to be acknowledged that using stereotypes in media representations makes it easier to disseminate clear messages, inform or entertain the audience. Hence, the use of gender-related or other group-related stereotypes is not only an issue of societal relations and equality but also an issue of information processing and message creation.   References/combination with other methods of data collection: Manual (e.g., Döring et al., 2016) and computational (e.g., Bhatia & Bhatia, 2020) content analyses of gender representations in mass media and social media can be combined. Furthermore, content analyses can be complemented with qualitative interviews and quantitative surveys to investigate both media creators’ and media audiences’ perceptions and evaluations of gender stereotypes in the media. Additionally, experimental studies are helpful to measure directly how different gender stereotypes in the media are perceived and evaluated by recipients and if and how they can affect their gender-related thoughts, feelings, and behaviors (Bast et al., 2021).   Example Studies for Manual Content Analyses: Acknowledging the multidimensionality and complexity of gender stereotypes in the media, this DOCA entry focuses on the analysis of gender displays in the tradition of Erving Goffman (1979, 1988). Goffman’s approach originally addressed press adversitements and was qualitative in nature. It has been adopted for quantitative content analyses and extended regarding relevant dimensions with a focus on press advertisments (Kang, 1997), magazine titles (Mortensen et al., 2020) as well as social media images such as selfies on Instagram (Döring et al., 2016; Baker & Walsh, 2018). Extending Goffman’s gender display framework to social media contexts and user-generated content does make sense from a theoretical point of view (Butkowski, 2020). Usually, dichotomous or polytomous variables are used to code stereotypical gender displays in the Goffman tradition, however, some content researchers also have developed and used rating scales for coding (Butkowski et al., 2020). So far, published codebooks with example pictures are scarce. Table 1. Example studies for manual content analyses. Coding Material Measure Operationalization (excerpt)  Reliability Source a)     Six categories of gender display according to Goffman (1979, 1988)     Relative size (between 2 or more persons) One person (usually the man) is depicted as larger in height and greater in girth through positioning or perspective of the image compared to the other person(s) (usually the woman). Can only be coded with 2 or more persons in the picture. Binary coding (1: yes; 2: no). Not available   N=500 selfies on Instagram Feminine touch One person (usually the woman) is pictured using their fingers and hands to trace the outlines of an object or to cradle it or to caress its surface or to touch their own body (e.g., their hair). The so-called feminine touch is not goal-oriented or functional. Binary coding (1: yes; 2: no).Example image for femine touch: Cohen’s Kappa = .79 Döring et al. (2016)   Function ranking (between 2 or more persons) One person (usually the man) is pictured in the executive or dominant role, the other person in the subordinate or assisting role (usually the woman). Can only be coded with 2 or more persons in the picture. Binary coding (1: yes; 2: no) Not available     Family(nuclear family of four persons) The typical nuclear family is depicted with mother, father, daughter, and son. Typically, closer bonds between mother and daughter on the one side, and father and son on the other side are depicted. Can only be coded with a whole family in the picture. Multidimensional qualitative variable that has not been adopted for quantitative coding yet. Not available   N=500 selfies on Instagram Ritualization of subordination One person (usually the woman) is depicted in a posture of subordination that deviates from a stable, upright position and includes lying/sitting postures and imbalance. Posture of subordination includes lying or sitting versus standing: Polytomous coding (1: lying, 2: sitting, 3: standing)Example image for lying posture: Imbalance in body posture includes canting positions and knee bending. Binary coding (1: yes; 2: no). Example image for imbalance posture: Lying, sitting, standing posture Cohen’s Kappa = 1.00   Imbalance posture: Cohen’s Kappa = .90 Döring et al. (2016) N=500 selfies on Instagram Licensed withdrawal One person (usually the woman) is depicted in a situation of licensed withdrawal meaning that she does not fully turn to the camera. This includes withdrawing gaze and loss of control. Withdrawing gaze means that one person (usually the woman) is depicted gazing away from the camera. Binary coding (1: yes; 2: no).Example image withdrawing gaze: Loss of control means that one person (usually the woman) is depicted expressing strong emotions implying that she is not fully focusing on the current scene . Binary coding (1: yes; 2: no).Example image loss of control: Withdrawing gaze: Cohen’s Kappa = 1.00   Loss of control: Cohen’s Kappa = 1.00 Döring et al. (2016) b)     Two additional gender display categories according to Kang (1997)           N=500 selfies on Instagram Body Display Body display of persons vary with the type of clothing. One person (usually the man) is depicted in full clothing. Binary coding (1: yes; 2: no). One person (usually the woman) is depicted in sparse clothing or nudity. Binary coding (1: yes; 2: no).Example image sparse closing Full clothing Cohen’s Kappa = .73   Sparse clothing: Cohen’s Kappa = .73   Döring et al. (2016)   Independence and self-assertiveness One person (usually the man) is depicted in a position of independence and self-assertivenesss. Binary coding (1: yes; 2: no). Not available   c)     Three categories of social media related gender stereotypes (Döring et al., 2016)           N=500 selfies on Instagram Kissing pout One person (usually the woman) is depicted showing a kissing pout (“duck face”). Binary coding (1: yes; 2: no). Example image for kissing pout: Cohen’s Kappa = 1.00 Döring et al. (2016) N=500 selfies on Instagram Muscle presentation One person (usually the man) is depicted presenting their muscles (e.g., biceps, sixpack). Binary coding (1: yes; 2: no). Example image for muscle presentation: Cohen’s Kappa = 1.00 Döring et al. (2016) N=500 selfies on Instagram Faceless portrayal One person (usually the woman) is depicted without the face in the picture. Binary coding (1: yes; 2: no). Example image for faceless portayal: Cohen’s Kappa = 1.00 Döring et al. (2016) Note. In order to ensure anonymity, no original Instagram posts are displayed. All example pictures shown are re-enactments to visually illustrate the categories and all protagonists gave their informed consent for publication of the pictures. The pictures are also used in the original study Döring et al. (2016).   The categories of gender display in the tradition of Erving Goffman (1979, 1988) can be complemented with further categories that go into more detail of physical appearance in terms of body type, attire or sexualization. Furthermore, additional dimensions of gender stereotyping such as occupations or activities can be added.   References Baker, S. A., & Walsh, M. J. (2018). ‘Good morning fitfam’: Top posts, hashtags and gender display on Instagram. New Media & Society, 20(12), 4553–4570. https://doi.org/10.1177/1461444818777514 Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall. Bandura, A. (2009). Social cognitive theory of mass communication. In J. Bryant & M. B. Oliver (Eds.), Communication series. Media effects: Advances in theory and research (3rd ed., pp. 94–124). Routledge. Bast, J., Oschatz, C., & Renner, A.‑M. (2021). Successfully overcoming the “bouble bind”? A mixed-method analysis of the self-presentation of female right-wing populists on Instagram and the impact on voter attitudes. Political Communication, 1–25. https://doi.org/10.1080/10584609.2021.2007190 Bhatia, N., & Bhatia, S. (2021). Changes in gender stereotypes over time: A computational analysis. Psychology of Women Quarterly, 45(1), 106–125. https://doi.org/10.1177/0361684320977178 Butkowski, C. P. (2020). Beyond “commercial realism”: Extending Goffman’s gender display framework to networked media contexts. Communication, Culture and Critique, 14(1), 89-108. Butkowski, C. P., Dixon, T. L., Weeks, K. R., & Smith, M.A. (2020). Quantifying the feminine self(ie): Gender display and social media feedback in young women’s Instagram selfies. New Media & Society, 22(5), 817-837. https://doi.org/10.1177/1461444819871669 Collins, R. L. (2011). Content analysis of gender roles in media: Where are we now and where should we go? Sex Roles, 64(3-4), 290–298. https://doi.org/10.1007/s11199-010-9929-5 Döring, N. (2019). Videoproduktion auf YouTube: Die Bedeutung von Geschlechterbildern [Video production on YouTube: The relevance of gender images]. In J. Dorer, B. Geiger, B. Hipfl, & V. Ratković (Eds.), Handbuch Medien und Geschlecht: Perspektiven und Befunde der feministischen Kommunikations- und Medienforschung (pp. 1–11). Springer Fachmedien. https://doi.org/10.1007/978-3-658-20712-0_53-1 Döring, N., & Mohseni, M. R. (2019). Fail videos and related video comments on YouTube: A case of sexualization of women and gendered hate speech? Communication Research Reports, 36(3), 254–264. https://doi.org/10.1080/08824096.2019.1634533 Döring, N., Reif, A., & Poeschl, S. (2016). How gender-stereotypical are selfies? A content analysis and comparison with magazine adverts. Computers in Human Behavior, 55, 955–962. https://doi.org/10.1016/j.chb.2015.10.001 Gerbner, G., & Gross, L. (1976). Living with television: The violence profile. The Journal of Communication, 26(2), 173–199. https://doi.org/10.1111/j.1460-2466.1976.tb01397.x Goffman, E. (1979). Gender advertisements. Harper & Row. Goffman, E. (1988). Gender advertisements (revised edition). Harpercollins College Div. Grau, S. L., & Zotos, Y. C. (2016). Gender stereotypes in advertising: A review of current research. International Journal of Advertising, 35(5), 761–770. https://doi.org/10.1080/02650487.2016.1203556 Kang, M.‑E. (1997). The portrayal of women’s images in magazine advertisements: Goffman’s gender analysis revisited. Sex Roles, 37(11-12), 979–996. https://doi.org/10.1007/BF02936350 Kim, K., & Lowry, D. T. (2005). Television commercials as a lagging social indicator: Gender role stereotypes in Korean television advertising. Sex Roles, 53(11-12), 901–910. https://doi.org/10.1007/s11199-005-8307-1 Maker, J. K., & Childs, N. M. (2003). A longitudinal content analysis of gender roles in children's television advertisements: A 27 year review. Journal of Current Issues & Research in Advertising, 25(1), 71–81. https://doi.org/10.1080/10641734.2003.10505142 Mitchell, M., & McKinnon, M. (2019). 'Human' or 'objective' faces of science? Gender stereotypes and the representation of scientists in the media. Public Understanding of Science (Bristol, England), 28(2), 177–190. https://doi.org/10.1177/0963662518801257 Mortensen, T. M., Ejaz, K., & Pardun, C. J. (2020). Quantifying gender stereotypes? Visually assessing stereotypes of women in People Magazine. Journal of Magazine Media, 21(1), 30–50. https://doi.org/10.1353/jmm.2020.0002 Rudy, R. M., Popova, L., & Linz, D. G. (2010). The context of current content analysis of gender roles: An introduction to a special issue. Sex Roles, 62(11-12), 705–720. https://doi.org/10.1007/s11199-010-9807-1 Sink, A., & Mastro, D. (2017). Depictions of gender on primetime television: A quantitative content analysis. Mass Communication and Society, 20(1), 3–22. https://doi.org/10.1080/15205436.2016.1212243 Ward, L. M., & Grower, P. (2020). Media and the development of gender role stereotypes. Annual Review of Developmental Psychology, 2(1), 177–199. https://doi.org/10.1146/annurev-devpsych-051120-010630 Windels, K. (2016). Stereotypical or just typical: How do US practitioners view the role and function of gender stereotypes in advertisements? International Journal of Advertising, 35(5), 864–887. https://doi.org/10.1080/02650487.2016.116085

    Abortion Attitudes (Media Content, User Comments)

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    The concept of "abortion attitudes" refers to an individual's or group's beliefs, opinions, and feelings regarding the practice of abortion (Jelen & Wilcox, 2003). Abortion here addresses abortion care in the form of medical (i.e., drug-induced) or surgical termination of an unwanted pregnancy, usually before the fetus is considered viable (i.e., able to survive outside the womb). People's attitudes towards abortion care can vary widely and are influenced by factors such as cultural, religious, moral, and personal beliefs, societal norms and values, as well as personal experiences and media representations (Adamczyk, Kim & Dillon, 2020; Ferree, Gamson, Gerhards & Rucht, 2002). Abortion and abortion attitudes are widely represented in the media, this includes news media, fictional media, and social media (Conti & Cahill, 2017). Attitudes towards abortion as they are held in the population and represented in the media are polarized and can be categorized broadly as pro-choice versus pro-life (Krolzik-Matthei, 2019): The pro-choice or pro-abortion attitude focuses on the pregnant woman/person and acknowledges her human rights to life, health and self-determination. Hence, the pro-choice attitude demands access to legal and safe abortions as a reproductive right for all women/persons who seek abortion care as a reproductive health service. The pro-choice position morally accepts abortions and politically favors the legalization of abortions. The pro-life or anti-abortion attitude focuses on the embryo (weeks 0 to 9 of the pregnancy) or the fetus (from week 10) and acknowledges its right to life. Hence, the pro-life attitude demands complete prohibition or at least heavy restriction of abortions, regardless of the life, health, and self-determination of the pregnant woman/person. The pro-life position morally condemns abortions and politically favors the criminalization of abortions in most or all cases. These two attitudes often manifest as general principles (or absolutist positions). But they also manifest in various shades of grey (situational positions), with some individuals and media representations supporting abortion under specific circumstances (such as cases of rape, incest, or severe fetal abnormalities) while opposing it in others (Rye & Underhill, 2020). In the context of ongoing political debates surrounding the legalization or criminalization of abortion (e.g., the overturning of Roe v. Wade in the USA in 2022), measuring attitudes towards abortion in media content remains a relevant and timely research topic, especially when it comes to popular and growing social media platforms such as TikTok (Wu & Byler, 2022).   Field of application/theoretical foundation One line of research investigates the various values underlying pro-life/pro-abortion and pro-choice/anti-abortion attitudes as represented in different media. This research approach employs theories from religion, moral philosophy, medical history, and/or feminism to extract the distinct arguments, frames, and metaphors used to defend and rationalize pro-choice versus pro-life attitudes (e.g., Brysk & Yang, 2023). Another line of research examines the associations between media representations of abortion attitudes on the one side and the audience’s attitudes about abortion on the other side (Döring, 2023; Döring & Kubitza, 2023; Pleasure et al., 2023), particularly in the context of pro- or anti-abortion campaigns (e.g., Reidy & Suiter, 2023) and online abortion education (Duggan, 2023). One relevant theory in this field is the social cognitive theory (Bandura 1986, 2009), which explains how media images of abortion can influence the audience’s perceptions of abortions. Additionally, theories of persuasion and education are applicable in this context.   References/combination with other methods of data collection Manual and automated content analyses of news media, fictional media, social media content, and social media user comments are essential for monitoring the potentially changing prevalence of various abortion attitudes in the public media sphere. These media content analyses can be combined with population surveys to explore associations between published opinion and public opinion on abortion. Furthermore, experimental studies are useful for directly measuring how recipients perceive and evaluate different media representations of abortion attitudes, and whether and how these representations can affect their own attitudes toward abortion.   Example Study for manual content analyses The example studies by Döring (2023) and Döring and Kubitza (2023) concentrate on the representation of abortion attitudes in German-language YouTube and TikTok videos, as well as the associated viewer comments (see Table 1). The measures presented were developed for YouTube and TikTok, but they are generic enough to be used across various social media platforms and even mass media channels. Depending on the research objective, more detailed measures can be developed and added. For examples, measures that cover the different circumstances under which people or media representations are willing to accept abortion as a moral and legal solution (such as in cases of rape, incest, or severe fetal abnormalities). This is relevant because abortion attitudes held by individuals and represented in the media are not always absolutist (i.e., categorical evaluations); sometimes, they are situationist, meaning that the specific conditions of the case play a significant role in the moral evaluation (Rye & Underhill, 2020).   Coding Material Measure Operationalization (excerpt) Reliability N = 167 top ranked German-language abortion videos on YouTube (n =  75) and TikTok (n = 92)   Type of Social Media Content Creator Polytomous variable “content creator type” (1: media professional, 2: health professional, 3: political/religious actor, 4: lay person)   n = 117 pretest sample Cohen’s Kappa = .84 Gwet’s AC1 = .88   Abortion Attitude in Social Media Content Polytomous variable “abortion attitude represented in YouTube/TikTok video” (1: pro-choice or pro-abortion [video predominantly argues in favor of legalization of abortion and/or the rights of the pregnant person], 2: pro-life or anti-abortion [video predominantly argues in favor of criminalization of abortion and/or the rights of the embryo/fetus], 3: ambivalent [video partly argues in favor of both pro-choice and pro-life positions; e.g., video covers both the attitude of a pro-life and a pro-choice activist], 4: neutral [video neither argues for or against the legalization or criminalization of abortions; e.g., video explains the procedure of surgical termination of an unwanted pregnancy and does not address moral or political evaluations], 5: unclear [the abortion attitude represented in the video remains unclear])   n = 117 pretest sample Cohen’s Kappa = .66 Gwet’s AC1 = .82 N = 807 most liked on-topic public user comments related to the N = 167 top ranked German-language abortion videos on YouTube (n = 326) and TikTok (n = 481)   Type of Commenting Social Media User Cannot be identified and coded due to practical and ethical considerations   n.a.   Abortion Attitude in Social Media User Comments Polytomous variable “abortion attitude represented in YouTube/TikTok user comments” (1: pro-choice / pro-abortion, 2: pro-life / anti-abortion, 3: ambivalent, 4: neutral, 5: unclear). Operationalization of the abortion attitudes in social media comments follows the same scheme used for social media videos (as described above).   n = 300 pretest sample Cohen’s Kappa = .55 Gwet’s AC1 = .81   References Adamczyk, A., Kim, C., & Dillon (2020). Examining Public Opinion about Abortion: A Mixed-Methods Systematic Review of Research over the Last 15 Years. Sociological Inquiry, 90 (4), 920–954. https://doi.org/10.1111/soin.12351 Bandura, A., & National Inst. of Mental Health. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice-Hall, Inc. Bandura, A. (2009). Social Cognitive Theory of Mass Communication. In J. Bryant & M. B. Oliver (Eds.), Communication Series. Media Effects: Advances in Theory and Research (3rd ed., 94–124). Routledge. Brysk, A., & Yang R. (2023). Abortion Rights Attitudes in Europe: Pro-Choice, Pro-Life, or Pro-Nation? Social Politics: International Studies in Gender, State & Society. https://doi.org/10.1093/sp/jxac047 Conti, J. A., & Cahill, E. (2017). Abortion in the Media. Current Opinion in Obstetrics & Gynecology, 29 (6), 427–430. https://doi.org/10.1097/GCO.0000000000000412 Döring, N., (2023). Online-Videos zum Schwangerschaftsabbruch: Anbieter, Botschaften und Publikumsreaktionen [Online Videos on Abortion: Creators, Messages, and Audience Reactions]. FORUM SexualaufklĂ€rung und Familienplanung: Informationsdienst der Bundeszentrale fĂŒr gesundheitliche AufklĂ€rung (BZgA) 1/2023, 41-47. https://doi.org/10.17623/BZgA_SRH:forum_2023-1_beitrag_onlinevideo_schwangerschaftsabbruch [Zugriff: 11.10.2023] Döring, N., & Kubitza, E. (2023). „Ich fĂŒhlte mich so alleine damit, aber dein Video hat mir geholfen – Der Schwangerschaftsabbruch auf YouTube und TikTok. ["I felt so alone with this, but your video helped me” – The Representation of Abortion on YouTube and TikTok]. merz – medien + erziehung. zeitschrift fĂŒr medienpĂ€dagogik, Online Article. https://www.merz-zeitschrift.de/swipe-des-monats/details/ich-fuehlte-mich-so-alleine-damit-aber-dein-video-hat-mir-geholfen [Zugriff: 11.10.2023] Duggan, J. (2023). Using TikTok to Teach about Abortion: Combatting Stigma and Miseducation in the United States and Beyond. Sex Education 23(1), 81-95. https://doi.org/10.1080/14681811.2022.2028614 Ferree, M.M., Gamson, W.A., Gerhards, J., & Rucht, D. (2002). Shaping Abortion Discourse: Democracy and the Public Sphere in Germany and the United States. Cambridge University Press. Jelen, T. G., & Wilcox, C. (2003). Causes and Consequences of Public Attitudes Toward Abortion: A Review and Research Agenda. Political Research Quarterly, 56 (4), 489–500. https://doi.org/10.1177/106591290305600410 Krolzik-Matthei, K. (2019). Abtreibungen in der Debatte in Deutschland und Europa [Abortions in the Debate in Germany and Europe]. Bundeszentrale fĂŒr politische Bildung (Hrsg.), Aus Politik und Zeitgeschichte (APuZ). https://www.bpb.de/shop/zeitschriften/apuz/290793/abtreibungen-in-der-debatte-in-deutschland-und-europa/ [Zugriff: 11.10.2023] Pleasure, Z. H., Becker, A., Johnson, D., Broussard, K., & Lindberg, L. (2023). How TikTok is Being Used to Talk About Abortion Post-Roe. https://doi.org/10.31235/osf.io/jy6vx [Zugriff: 11.10.2023] Reidy, T., & Suiter, J. (2023). Does Social Media Use Matter? A Case Study of the 2018 Irish Abortion Referendum. Media and Communication, 11 (1), 81–85. https://doi.org/10.17645/mac.v11i1.6653 Rye, B.J., & Underhill, A. (2020). Pro-choice and Pro-life Are Not Enough: An Investigation of Abortion Attitudes as a Function of Abortion Prototypes. Sexuality & Culture 24, 1829–1851. https://doi.org/10.1007/s12119-020-09723-7 Wu, Y. & Byler, D. (2022). What We Found When Analyzing 1,000 Viral TikToks on #Abortion. The Washington Post, 22th October 2022. https://www.washingtonpost.com/opinions/interactive/2022/tiktok-abortion-debate-gen-z/ [Zugriff: 11.10.2023]   Funding: This entry was created as part of a larger research project lead by the author on the representation of sexual and reproductive health issues on social media, led by the author and funded by the Federal Centre for Health Education (BZgA) from 2023 to 2026. The name of the project is EMSA (“Erstes Mal, Menstruation und Schwangerschaftsabbruch in Sozialen Medien” = sexual debut, menstruation, and abortion on social media)

    Geschlechtsspezifische Hassrede in YouTube- und YouNow-Kommentaren: Ergebnisse von zwei Inhaltsanalysen

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    Online hate speech in general, and gendered online hate speech in particular, have become an issue of growing concern both in public and academic discourses. However, although YouTube is the most important social media platform today and the popularity of social live streaming services (SLSS) such as Twitch, Periscope and YouNow is constantly growing, research on gendered online hate speech on video platforms is scarce. To bridge this empirical gap, two studies investigated gendered online hate speech in video comments on YouTube and YouNow, thereby systematically replicating a study by Wotanis and McMillan (2014). Study 1 investigated YouTube in the form of a content analysis of N = 8,000 publicly available video comments that were addressed towards four pairs of female and male German-speaking YouTubers within the popular genres Comedy, Gaming, HowTo & Style, and Sports [Fitness]. Study 2 examined YouNow, with a quantitative content analysis of N = 6,844 publicly available video comments made during the video streams of 16 female and 14 male popular German-speaking YouNowers. Study 1 successfully replicated the findings of Wotanis and McMillan (2014) that compared to male You-Tubers, female YouTubers received more negative video comments (including sexist, racist, and sexually aggressive hate speech) (H1a). In addition, they received fewer positive video comments regarding personality and video content but more positive video comments regarding physical appearance (H2a). Study 2 partly confirmed the earlier findings: It found that, compared to male YouNowers, the video comments received by female YouNowers were more sexist and sexually aggressive, but not generally more hostile or negative (H1b). They received more positive video comments regarding their physical appearance but did not receive fewer positive video comments regarding their personality or the content of their videos (H2b). With some exceptions, the findings of study 2 were comparable to the findings of study 1 (RQ1). In both studies, most effect sizes were small. Overall, females on the video platforms YouTube and YouNow seem to be disproportionately affected by both hostile and benevolent sexism expressed in viewer comments. The results are in line with the Expectation States Theory and the Ambivalent Sexism Theory. The total number of public hate comments was probably underestimated because inappropriate comments can be deleted by moderators and users. Future research directions and practical implications are discussed. Supplementary material can be retrieved from https://osf.io/da8tw.Online-Hassrede im Allgemeinen und geschlechtsspezifische Hassrede im Speziellen sind zu Problemen geworden, die mit zunehmender Besorgnis in öffentlichen und akademischen Diskursen behandelt werden. Dennoch gibt es bisher kaum Studien zu geschlechtsspezifischer Hassrede auf Videoplattformen, und dass, obwohl YouTube heutzutage die wichtigste Social-Media-Plattform darstellt und die PopularitĂ€t von Social Live Streaming Services (SLSS) wie z. B. Twitch, Periscope und YouNow stetig wĂ€chst. Um diese empirische LĂŒcke zu fĂŒllen, untersuchten zwei Studien geschlechtsspezifische Hassrede in Videokommentaren auf YouTube bzw. YouNow und replizierten dabei systematisch eine VorlĂ€uferstudie von Wotanis und McMillan (2014). Studie 1 untersuchte YouTube in Form einer Inhaltsanalyse von N = 8.000 öffentlich sichtbaren Videokommentaren, die sich an vier Paarungen weiblicher und mĂ€nnlicher deutschsprachiger YouTuber*innen aus den beliebten Genres Comedy, Gaming, HowTo & Style und Sports [Fitness] richteten. Studie 2 untersuchte YouNow mit einer quantitativen Inhaltsanalyse von N = 6.844 öffentlich zugĂ€nglichen Videokommentaren, die wĂ€hrend der Video-Streams von 16 weiblichen und 14 mĂ€nnlichen populĂ€ren deutschsprachigen YouNower*innen geĂ€ußert wurden. Studie 1 konnte erfolgreich die Befunde von Wotanis und McMillan (2014) replizieren, dass weibliche im Vergleich zu mĂ€nnlichen YouTuber*innen mehr negative Videokommentare (inklusive sexistischer, rassistischer, und sexuell aggressiver Hassrede) erhielten (H1a). Außerdem erhielten sie weniger positive Videokommentare zu ihrer Persönlichkeit und dem Inhalt ihrer Videos, aber mehr positive Videokommentare hinsichtlich ihres Aussehens (H2a). Studie 2 konnte die vorherigen Befunde teilweise bestĂ€tigen: Es wurde festgestellt, dass weibliche YouNower*innen im Vergleich zu mĂ€nnlichen YouNower*innen mehr sexistische und sexuell aggressive Video-Kommentare erhalten, aber nicht generell mehr feindselige oder negative Video-Kommentare (H1b). Sie erhielten außerdem mehr positive Videokommentare zu ihrem Aussehen, aber nicht weniger positive Videokommentare zu ihrer Persönlichkeit oder dem Inhalt ihrer Videos (H2b). Mit einigen Ausnahmen waren die Ergebnisse von Studie 1 mit denen aus Studie 2 vergleichbar (RQ1). In beiden Studien waren die meisten EffektstĂ€rken klein. Insgesamt scheinen Frauen auf den beiden Video-Plattformen YouTube und You-Now disproportional von feindseligem und wohlwollendem Sexismus betroffen zu sein, der in den Kommentaren des Publikums zum Ausdruck kommt. Die Ergebnisse stehen im Einklang mit der Theorie der ErwartungszustĂ€nde und der Theorie des ambivalenten Sexismus. Die Gesamtzahl der öffentlichen Hasskommentare wurde in dieser Studie wahrscheinlich unterschĂ€tzt, da diese von Moderator*innen und Nutzer*innen gelöscht werden können. ZukĂŒnftige Forschungsmöglichkeiten und praktische Implikationen werden diskutiert. ZusĂ€tzliches Material kann unter https://osf.io/da8tw abgerufen werden

    Iconography of Child Sexual Abuse in the News (Justice and Crime Reporting)

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    Child sexual abuse (CSA) is a major global problem (Barth et al., 2013). Therefore, it is important for researchers in communication science to systematically examine the representation of the CSA issue in the media using manual and computational methods of content analysis. According to previous review papers (Popović, 2018; Weatherred, 2015), existing content-analytical studies are mostly manual and limited to newspaper articles and the text level. Currently, it is unclear what kind of visual representations are used to illustrate the CSA issue in the media. We therefore present a tested new instrument to analyze the dominant image motifs (= iconography) in CSA news media coverage (Döring & Walter, 2021).   Field of application/theoretical foundation: CSA reporting often focuses on specific cases of CSA (Dorfman et al., 2011). Therefore, media reporting on CSA mainly falls into the area of justice and crime reporting. From a theoretical perspective, CSA representations in the media are mostly analyzed based on framing theory (Entman, 1993). Respective studies investigate which aspects of the CSA problem are emphasized in the media and which are neglected. Research shows that stereotypes and myths are spread and episodic framing (= focus on individual cases) is often prevalent, while thematic framing (= representation of CSA as a societal issue) is missing in the media coverage (Popović, 2018; Weatherred, 2015). There are hardly any empirical findings on visual framing and the iconography used in CSA media reporting (Döring & Walter, 2021). However, some more research exists on the broader issue of visual representations of sexual violence in the news (e.g., Schwark, 2017).   References/combination with other methods of data collection: Generally, the text analysis method dominates in the field of justice and crime reporting (e.g., portrayals of crimes in newspapers vs. television; Pollak & Kubrin, 2007). The few available image analyses in this field have not yet addressed CSA but focus on different crimes (e.g., portrayal of the 9/11 terrorist attack and its commemoration in the press; Ammann, 2015). In addition to pure content analyses, combinations with other methods of data collection that incorporate the communicator’s perspective can contribute to a more in-depth investigation of the CSA iconography. For example, interviews with journalists on how they select CSA-related images for news reporting would be insightful, but such studies are currently lacking. Equally important are combinations of content analyses with data collection methods that focus on possible media effects on the recipients, for example by conducting experiments exploring the effects of different textual and visual CSA representations. Although there are experimental studies on the effects of textual elements of CSA reporting (e.g., different perpetrator and victim constellations; Scheufele, 2005), there is a lack of studies on the effects of visual elements.   Example studies: Researchers interested in conducting content analyses about CSA reporting in general – and visualizations of the CSA problem in particular – can consult the following example studies: review papers on content analyses of CSA media reporting (Popović, 2018; Weatherred, 2015), CSA-related content analyses focusing on textual elements (Dorfman et al., 2011; Mejia et al., 2012), CSA-related content analyses focusing on both textual and visual elements (Popović, 2021: explained below), CSA-related content analyses focusing on visual elements and in particular the dominant image motifs in terms of the CSA iconography (Döring & Walter, 2021: explained below).   Information on Popović, 2021 Authors: Stjepka Popović Research question: How are victims of child sexual abuse represented in the press in Croatia? Object of analysis: Probabilistic cluster sample of N = 1 159 CSA-related news reports (text and photos) of the six most popular daily printed Croatian newspapers Time frame of analysis: 2007-2016   Info about photo-related variables Variable name/definition: Victim endangering CSA news reporting practices linked to photos were measured with three mutually exclusive variables (p. 238). Indirect disclosure of victim’s identity: photo of either a) victim’s home; b) location of abuse; c) family members, relatives or neighbors Direct disclosure of victim’s identity: a) blurred photo of victim OR b) photo of victim taken from the back Sexually explicit material: a) photographs or illustrations of the child in explicit poses or underwear OR b) photographs or illustrations of abuse OR c) forensic drawings of victim Level of analysis: Symbolic and documentary images. Values: 0 = absent, 1 = present (binary coding for each image) Reliability: Krippendorff’s Alpha: 0.90 for entire coding matrix   Information on Döring & Walter, 2021 Authors: Nicola Döring & Roberto Walter Research question: Which iconography (i.e. set of main types of image motifs) is used to visualize the issue of child sexual abuse in newspaper articles? Object of analysis: Convenience sample of N = 1 437 CSA-related online news reports including N = 419 stock photos from different German-language newspapers and news magazines (e.g., Die Zeit, Bild, taz, SĂŒddeutsche, Spiegel, Focus) Time frame of analysis: 2014-2018   Info about image-related variables Variable name/definition: Iconography of child sexual abuse in the news (set of 7 mutually exclusive image motif types categorized into three image motif groups; see Table 1). The complete codebook, data and analysis scripts are available at https://osf.io/g2cxa/ (Döring & Walter, 2021). Level of analysis: Symbolic image. Values: 0 = absent, 1= present (binary coding for each image motif type) Reliability: Holsti: 0.94 – 0.98; Gwet’s AC1: 0.90 – 0.98 (see Table 1 for each image motif type)   Table 1. Codebook for the iconography of child sexual abuse in the news Variables: Types of image motifs Variable descriptions plus example images Values Reliability - Holsti- Gwet’s AC1 1. Context of the crime       1.1 Real-world context Code as present if the image shows the real-world context of CSA (e.g., a church, school or swimming pool) but does not focus on the people involved. 0 = absent 1 = present .94 .91 1.2 Virtual context Code as present if the image shows the virtual context of CSA (e.g., a laptop, keyboard or webcam) but does not focus on the people involved. 0 = absent 1 = present .98 .98 2. Course of the crime and people involved       2.1 Perpetrator before/during the crime Code as present if the image shows the perpetrator before/during the crime but does not focus on the context or victim. 0 = absent 1 = present -a - 2.2 Victim before/during the crime Code as present if the image shows the victim before/during the crime but does not focus on the context or perpetrator. 0 = absent 1 = present .96 .95 2.3 Perpetrator and victim before/during the crime Code as present if the image shows the perpetrator and the victim before/during the crime but does not focus on the context. 0 = absent 1 = present .94 .90 3. Consequences of the crime       3.1 Consequences for the victim Code as present if the image shows the consequences of the crime for the victim (e.g., physical and emotional pain, trauma). 0 = absent 1 = present .94 .93 3.2 Consequences for the perpetrator Code as present if the image shows the consequences of the crime for the perpetrator (e.g., arrest, conviction). 0 = absent 1 = present .98 .97 Note. aReliability for this variable could not be calculated, because the image motif was not present in the pretest sample. Depending on the research question, the whole set of seven main types of image motifs of the CSA iconography can be measured or only selected motifs can be chosen as all binary variables are independent from each other. Also, new motifs can be added. For example, visualizations that illustrate the societal relevance of CSA (e.g., info graphics that show prevalence rates) or visualizations of primary, secondary and tertiary prevention methods (e.g., therapy for victims and/or perpetrators) could be added as further image motif types. For a more granular quantitative analysis of a large-scale sample of newspaper articles, it is possible to code not only the image motif type (e.g., real-world context), but also the individual motifs that belong to this type (e.g., church, school, swimming pool, sports club). Last but not least, for selected image motif types an additional qualitative image analysis might be fruitful. For example, the image type “victim before/during the crime” often operates with objectification and sexualization of the victim than can be further explored qualitatively (e.g., type of clothing of the victim, camera angle and perspective).   References Ammann, I. (2015). Im Bilde gedacht. Der Gedenktag 9/11 in der deutschen und US-amerikanischen Pressefotografie [Picturing commemoration. A comparative analysis of anniversary 9/11 in German and US-American press photography]. Studies in Communication | Media, 4(4), 436–453. https://doi.org/10.5771/2192-4007-2015-4-436 Barth, J., Bermetz, L., Heim, E., Trelle, S., & Tonia, T. (2013). The current prevalence of child sexual abuse worldwide. A systematic review and meta-analysis. International Journal of Public Health, 58(3), 469–483. https://doi.org/10.1007/s00038-012-0426-1 Dorfman, L., Mejia, P., Cheyne, A., & Gonzalez, P. (2011). Case by Case: News coverage of child sexual abuse, 2007-2009. http://www.bmsg.org/sites/default/files/bmsg_issue19.pdf Döring, N., & Walter, R. (2021). Ikonografien des sexuellen Kindesmissbrauchs: Symbolbilder in Presseartikeln und PrĂ€ventionsmaterialien [Iconographies of child sexual abuse: Symbolic images in press articles and prevention materials]. Studies in Communication and Media, 10(3), 362-405. https://doi.org/10.5771/2192-4007-2021-3-362 Entman, R. M. (1993). Framing: Toward Clarification of a Fractured Paradigm. Journal of Communication, 43(4), 51–58. https://doi.org/10.1111/J.1460-2466.1993.TB01304.X Mejia, P., Cheyne, A., & Dorfman, L. (2012). News Coverage of Child Sexual Abuse and Prevention, 2007-2009. Journal of Child Sexual Abuse, 21(4), 470–487. https://doi.org/10.1080/10538712.2012.692465 Pollak, J. M. , & Kubrin, C. E. (2007). Crime in the news: How crimes, offenders and victims are portrayed in the media. Journal of Criminal Justice and Popular Culture, 14, 59–83. Popović, S. (2018). Child sexual abuse news. A systematic review of content analysis studies. Journal of Child Sexual Abuse, 27(7), 752–777. https://doi.org/10.1080/10538712.2018.1486935 Popović, S. (2021). Presentation of Victims in the Press Coverage of Child Sexual Abuse in Croatia. Journal of Child Sexual Abuse, 30(2), 230–251. https://doi.org/10.1080/10538712.2020.1871459 Scheufele, B. (2005). Sexueller Missbrauch: Mediendarstellung und Medienwirkung [Child Sexual Abuse: Media Representations and Media Effects] (1st Ed.). VS Verlag fĂŒr Sozialwissenschaften. Schwark, S. (2017). Visual Representations of Sexual Violence in Online News Outlets. Frontiers in Psychology, 8, Article 774. https://doi.org/10.3389/fpsyg.2017.00774 Weatherred, J. L. (2015). Child sexual abuse and the media: A literature review. Journal of Child Sexual Abuse, 24(1), 16–34. https://doi.org/10.1080/10538712.2015.97630

    Alcohol Portrayals on Social Media (Social Media)

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    The depiction of alcohol is the focus of a growing number of content analyses in the field of social media research. Typically, the occurrence and nature of alcohol representations are coded to measure the prevalence, normalization, or even glorification of alcohol and its consumption on different social media platforms (Moreno et al., 2016; Westgate & Holliday, 2016) and smartphone apps (Ghassemlou et al., 2020). But social media platforms and smartphone apps also play a role in the prevention of alcohol abuse when they disseminate messages about alcohol risks and foster harm reduction, abstinence, and sobriety (Davey, 2021; Döring & Holz, 2021; Tamersoy et al., 2015; Westgate & Holliday, 2016).   Field of application/theoretical foundation: Social Cognitive Theory (SCT; Bandura 1986, 2009) as the dominant media effects theory in communication science, is applicable and widely applied to social media representations of alcohol: According to SCT, positive media portayals of alcohol and attractive role models consuming alcohol can influence the audience’s relation to alcohol. That’s why positive alcohol portayals in the media are considered a public health threat as they can foster increased and risky alcohol consumption among media users in general and young people in particular. The negative health impact predicted by SCT depends on different aspects of alcohol portrayals on social media that have been traditionally coded in manual content analyses (Beullens & Schepers, 2013; Mayrhofer & Naderer, 2019; Moreno et al., 2010) and most recently by studies relying on computational methods for content analysis (e.g. Ricard & Hassanpour, 2021). Core aspects of alcohol representations on social media are: a) the type of communicator / creator of alcohol-related social media content, b) the overall valence of the alcohol portrayal, c) the people consuming alcohol, d) the alcohol consumption behaviors, e) the social contexts of alcohol consumption, f) the types and brands of consumed alcohol, g) the consequences of alcohol consumption, and h) alcohol-related consumer protection messages in alcohol marketing (Moreno et al., 2016; Westgate & Holliday, 2016). For example, a normalizing portrayal shows alcohol consumption as a regular and normal behavior of diverse people in different contexts, while a glorifying portrayal shows alcohol consumption as a behavior that is strongly related to positive effects such as having fun, enjoying social community, feeling sexy, happy, and carefree (Griffiths & Casswell, 2011). While criticism of glorifying alcohol portrayals in entertainment media (e.g., music videos; Cranwell et al., 2015), television (e.g., Barker et al., 2021), and advertising (e.g., Curtis et al., 2018; Stautz et al., 2016) has a long tradition, the concern about alcohol representations on social media is relatively new and entails the phenomenon of alcohol brands and social media influencers marketing alcohol (Critchlow & Moodie, 2022; Turnwald et al., 2022) as well as ordinary social media users providing alcohol-related self-presentations (e.g., showing themselves partying and drinking; Boyle et al., 2016). Such alcohol-related self-presentations might elicit even stronger identification and imitation effects among social media audiences compared to regular advertising (Griffiths & Casswell, 2011). Because of its psychological and health impact, alcohol-related social media content – and alcohol marketing in particular – is also an issue of legal regulation. The World Health Organization states that “Europe is the heaviest-drinking region in the world” and strongly advocates for bans or at least stricter regulations of alcohol marketing both offline and online (WHO, 2020, p. 1). At the same time, the WHO points to the problem of clearly differentiating between alcohol marketing and other types of alcohol representations on social media. Apart from normalizing and glorifying alcohol portayals, there are also anti-alcohol posts and comments on social media. They usually point to the health risks of alcohol consumption and the dangers of alcohol addiction and, hence, try to foster harm reduction, abstincence and sobriety. While such negative alcohol portayals populate different social media platforms, an in-depth investigation of the spread, scope and content of anti-alcohol messages on social media is largely missing (Davey, 2021; Döring & Holz, 2021; Tamersoy et al., 2015).   References/combination with other methods of data collection: Manual and computational content analyses of alcohol representations on social media platforms can be complemented by qualitative interview and quantitative survey data addressing alcohol-related beliefs and behaviors collected from social media users who a) create and publish alcohol-related social media content and/or b) are exposed to or actively search for and follow alcohol-related social media content (e.g., Ricard & Hassanpour, 2021; Strowger & Braitman, 2022). Furthermore, experimental studies are helpful to directly measure how different alcohol-related social media posts and comments are perceived and evaluated by recipients and if and how they can affect their alcohol-related thoughts, feelings, and behaviors (Noel, 2021). Such social media experiments can build on respective mass media experiments (e.g., Mayrhofer & Naderer, 2019). Insights from content analyses help to select or create appropriate stimuli for such experiments. Last but not least, to evaluate the effectiveness of alcohol marketing regulations, social media content analyses conducted within a longitudinal or trend study design (including measurements before and after new regulations came into effect) should be preferred over cross-sectional studies (e.g., Chapoton et al., 2020).   Example Studies for Manual Content Analyses: Coding Material Measure Operationalization (excerpt) Reliability Source a) Creators of alcohol-related social media content Extensive explorations on Facebook, Instagram and TikTok Creators of alcohol-related social media content on Facebook, Instagram and TikTok Polytomous variable “Type of content creator” (1: alcohol industry; 2: media organization/media professional; 3: health organization/health professional; 4: social media influencer; 5: ordinary social media user; 6: other) Not available Döring & Tröger (2018)   Döring & Holz (2021) b)     Valence of alcohol-related social media content N = 3 015 Facebook comments   N = 100 TikTok videos Valence of alcohol-related social media content (posts or comments) Binary variable “Valence of alcohol-related social media content” (1: positive/pro-alcohol sentiment; 2: negative/anti-alcohol sentiment) Cohen’s Kappa average of .72 for all alcohol-related variables in codebook* Döring & Holz (2021)   *Russell et al. (2021) c) People consuming alcohol N = 160 Facebook profiles (profile pictures, personal photos, and text) Portrayal of people consuming alcohol on Facebook profiles Binary variable “Number of persons on picture” (1: alone; 2: with others) Cohen’s Kappa > .90 Beullens & Schepers (2013) d) Alcohol consumption behaviors N = 160 Facebook profiles (profile pictures, personal photos, and text) Type of depicted alcohol use/consumption Polytomous variable “Type of depicted alcohol use/consumption” (1: explicit use such as depiction of person drinking alcohol; 2: implicit use such as depiction of alcohol bottle on table; 3: alcohol logo only) Cohen’s Kappa = .89 Beullens & Schepers (2013) N = 100 TikTok videos   Multiple alcoholic drinks consumed per person Binary variable “Multiple alcoholic drinks consumed per person” as opposed to having only one drink or no drink per person (1: present; 2: not present) Cohen’s Kappa average of .72 for all alcohol-related variables in codebook Russell et al. (2021) N = 100 TikTok videos Alcohol intoxication Binary variable “Alcohol intoxication” (1: present; 2: not present) Cohen’s Kappa average of .72 for all alcohol-related variables in codebook Russell et al. (2021) N = 4 800 alcohol-related Tweets Alcohol mentioned in combination with other substance use Binary variable “Alcohol mentioned in combination with tobacco, marijuana, or other drugs” (1: yes; 2: no) Cohen’s Kappa median of .73 for all pro-drinking variables in codebook Cavazos-Rehg et al. (2015) e) Social contexts of alcohol consumption N = 192 Facebook and Instagram profiles (profile pictures, personal photos, and text) Portrayal of social evaluative contexts of alcohol consumption on Facebook and Instagram profiles Polytomous variable “Social evaluative context” (1: negative context such as someone looking disapprovingly at a drunk person; 2: neutral context such as no explicit judgment or emotion is shown; 3: positive context such as people laughing and toasting with alcoholic drinks) Cohen’s Kappa ranging from .68 to .91 for all variables in codebook Hendriks et al. (2018), based on previous work by Beullens & Schepers (2013) N = 51 episodes with a total of N = 1 895 scenes of the American adolescent drama series “The OC” Portrayal of situational contexts of alcohol consumption in scenes of a TV series Polytomous variable “Setting of alcohol consumption” (1: at home; 2: at adult / youth party; 3: in a bar; 4: at work; 5: at other public place)   Polytomous variable “Reason of alcohol consumption” (1: celebrating/partying; 2: habit; 3: stress relief; 4: social facilitation) Cohen’s Kappa for setting of alcohol consumption .90   Cohen’s Kappa for reason of alcohol consumption .71 Van den Bulck et al. (2008) f) Types and brands of consumed alcohol N = 17 800 posts of Instagram influencers and related comments Portrayal of different alcohol types and alcohol brands in Instagram posts   Polytomous variable “Alcohol type” (1: wine; 2: beer; 3: cocktails; 4: spirits; 5: non-alcoholic drinks/0% alcohol)   Binary variable “Alcohol brand visibility” (1: present if full brand name, recognizable logo, or brand name in header or tag are visible; 2: non-present)   String variable “Alcohol brand name” (open text coding) Krippendorff’s Alpha ranging from .69 to 1.00 for all variables in codebook Hendriks et al. (2019) g) Consequences of alcohol consumption N = 400 randomly selected public MySpace profiles Portayal of consequences of alcohol consumption on MySpace profiles   Five individually coded binary variables for different consequences associated with alcohol use (1: present; 2: not present):   a) “Positive emotional consequence highlighting positive mood, feeling or emotion associated with alcohol use”   b) “Negative emotional consequence highlighting negative mood, feeling or emotion associated with alcohol use”   c) “Positive social consequences highlighting perceived social gain associated with alcohol use”   d) “Negative social consequences highlighting perceived poor social outcomes associated with alcohol use”   e) “Negative physical consequences describing adverse physical consequences or outcomes associated with alcohol use” Cohen’s Kappa ranging from 0.76 to 0.82 for alcohol references and alcohol use Moreno et al. (2010) h) Alcohol-related consumer protection messages in alcohol marketing N = 554 Tweets collected from 13 Twitter accounts of alcohol companies in Ireland Alcohol-related consumer protection messages in alcohol marketing (covers both mandatory and voluntary messages depending on national legislation)   Four individually coded binary variables for different alcohol-related consumer protection messages in alcohol marketing (1: present; 2: not present):   a) “Warning about the risks/danger of alcohol consumption”   b) “Warning about the risks/danger of alcohol consumption when pregnant”   c) “Warning about the link between alcohol consumption and fatal cancers”   d) “Link/reference to website with public health information about alcohol” Not available   Critchlow & Moodie (2022)   The presented measures were developed for specific social media platforms, but are so generic that they can be used across different social media platforms and even across mass media channels such as TV, cinema, and advertisement. The presented measures cover different aspects of media portrayals of alcohol and can be used individually or in combination. Depending on the research aim, more detailed measures can be developed and added: for example, regarding the media portrayal of people consuming alcohol, additional measures can code people’s age, gender, ethnicity and further characteristics relevant to the respective research question. In the course of a growing body of content analyses addressing alcohol-related prevention messages on social media, respective measures can be added as well.   References Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall. Bandura, A. (2009). Social cognitive theory of mass communication. In J. Bryant & M. B. Oliver (Eds.), Communication series. Media effects: Advances in theory and research (3rd ed., pp. 94–124). Routledge. Barker, A. B., Britton, J., Thomson, E., & Murray, R. L. (2021). Tobacco and alcohol content in soap operas broadcast on UK television: A content analysis and population exposure. Journal of Public Health (Oxford, England), 43(3), 595–603. https://doi.org/10.1093/pubmed/fdaa091 Boyle, S. C., LaBrie, J. W., Froidevaux, N. M., & Witkovic, Y. D. (2016). Different digital paths to the keg? How exposure to peers' alcohol-related social media content influences drinking among male and female first-year college students. Addictive Behaviors, 57, 21–29. https://doi.org/10.1016/j.addbeh.2016.01.011 Beullens, K., & Schepers, A. (2013). Display of alcohol use on Facebook: A content analysis. Cyberpsychology, Behavior and Social Networking, 16(7), 497–503. https://doi.org/10.1089/cyber.2013.0044 Cavazos-Rehg, P. A., Krauss, M. J., Sowles, S. J., & Bierut, L. J. (2015). "Hey everyone, I'm drunk." An evaluation of drinking-related Twitter chatter. Journal of Studies on Alcohol and Drugs, 76(4), 635–643. https://doi.org/10.15288/jsad.2015.76.635 Chapoton, B., Werlen, A.‑L., & Regnier Denois, V. (2020). Alcohol in TV series popular with teens: A content analysis of TV series in France 22 years after a restrictive law. European Journal of Public Health, 30(2), 363–368. https://doi.org/10.1093/eurpub/ckz163 Cranwell, J., Murray, R., Lewis, S., Leonardi-Bee, J., Dockrell, M., & Britton, J. (2015). Adolescents' exposure to tobacco and alcohol content in YouTube music videos. Addiction (Abingdon, England), 110(4), 703–711. https://doi.org/10.1111/add.12835 Critchlow, N., & Moodie, C. (2022). Consumer protection messages in alcohol marketing on Twitter in Ireland: A content analysis. Drugs: Education, Prevention and Policy, 1–8. https://doi.org/10.1080/09687637.2022.2028730 Curtis, B. L., Lookatch, S. J., Ramo, D. E., McKay, J. R., Feinn, R. S., & Kranzler, H. R. (2018). Meta-analysis of the association of alcohol-related social media use with alcohol consumption and alcohol-related problems in adolescents and young adults. Alcoholism, Clinical and Experimental Research, 42(6), 978–986. https://doi.org/10.1111/acer.13642 Davey, C. (2021). Online sobriety communities for women's problematic alcohol use: A mini review of existing qualitative and quantitative research. Frontiers in Global Women's Health, 2, 773921. https://doi.org/10.3389/fgwh.2021.773921 Döring, N., & Tröger, C. (2018). Zwischenbericht: DurchfĂŒhrung und Ergebnisse der summativen Evaluation des Facebook-Kanals „Alkohol? Kenn dein Limit.“ [Intermediate report: Implementation and results of the summative evaluation of the Facebook channel "Alcohol? Know your limit."]. Döring, N., & Holz, C. (2021). Alkohol in sozialen Medien: Wo ist der Platz fĂŒr PrĂ€vention? [Alcohol in social media: Where is the space for prevention?]. Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, 64(6), 697–706. https://doi.org/10.1007/s00103-021-03335-8 Ghassemlou, S., Marini, C., Chemi, C., Ranjit, Y. S., & Tofighi, B. (2020). Harmful smartphone applications promoting alcohol and illicit substance use: A review and content analysis in the United States. Translational Behavioral Medicine, 10(5), 1233–1242. https://doi.org/10.1093/tbm/ibz135 Griffiths, R., & Casswell, S. (2010). Intoxigenic digital spaces? Youth, social networking sites and alcohol marketing. Drug and Alcohol Review, 29(5), 525–530. https://doi.org/10.1111/j.1465-3362.2010.00178.x Hendriks, H., van den Putte, B., Gebhardt, W. A., & Moreno, M. A. (2018). Social drinking on social media: Content analysis of the social aspects of alcohol-related posts on Facebook and Instagram. Journal of Medical Internet Research, 20(6), e226. https://doi.org/10.2196/jmir.9355 Hendriks, H., Wilmsen, D., van Dalen, W., & Gebhardt, W. A. (2019). 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    Die Wirksamkeit von Medienbildungsinitiativen: Erfolge, Probleme und LösungsansÀtze

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    Neben der Persönlichkeitsbildung obliegt der Schule ein Qualifizierungsauftrag (KMK 2012, 3). Im Zusammenhang dieses Auftrags, SchĂŒlerinnen und SchĂŒler auf das (Berufs-) Leben vorzubereiten, hielten digitale Medien Einzug in nahezu alle Schulformen. Dort sollen sie neben der Förderung der Medienkompetenz in allen ihren AusprĂ€gungen auf Seiten der SchĂŒlerinnen und SchĂŒler, zudem die Lehr- und Lernkultur verbessern. Mit Hilfe landes- und stĂ€dteweiter Initiativen wird dabei die Medienintegration und konkrete Mediennutzung vorangetrieben, wie bspw. durch die Medienbildungsinitiative der Stadt Frankfurt am Main, deren Erfolge, Probleme und LösungsansĂ€tze nach zehnjĂ€hrigem Bestehen in diesem Artikel betrachtet werden. Ziel war es dabei, den aktuellen Entwicklungsstand, noch bestehende Probleme und vor allem deren mögliche Lösung aus Perspektive der LehrkrĂ€fte darzustellen. Insgesamt wurden MĂ€ngel bei der IT-Infrastruktur, den mediendidaktischen UnterstĂŒtzungsangeboten und hinderliche organisatorische Rahmenbedingungen identifiziert

    [Rezension von: Utz, Sonja, Soziale Identifikation mit virtuellen Gemeinschaften ...]

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    Vorgestellt werden zwei Studien, die sich mit dem Gemeinschafts-Charakter von MUDs (Multi User Domains/Dungeons) – einer bestimmten Gruppe von Mehrpersonen-Online-Spielen – befassen. Die eine Studie konzentriert sich auf die soziale Identifikation der MUDMitglieder mit ihren jeweiligen MUDs, wobei standardisierte Fragebogen-Erhebungen bzw. Fragebogen-Experimente mit 217 Muddern und 110 Nicht-Muddern zugrunde liegen (UTZ 1999). Die andere Studie untersucht Prozesse der sozialen Integration in drei ausgewĂ€hlten MUDs mit Hilfe teilnehmender Feldbeobachtungen sowie persönlicher Leitfaden-Interviews und standardisierter Fragebogen-Erhebungen an 40 erfahrenen Mudderinnen und Muddern (GÖTZENBRUCKER 2001). Beide Studien weisen nach, dass sich in MUD-Umgebungen sowohl auf der Ebene des individuellen Erlebens als auch auf der Ebene der sozialen Praxis bekannte PhĂ€nomene der Zusammengehörigkeit und Gemeinschaftsbildung zeigen. Diese virtuelle Vergemeinschaftung geht bei den Untersuchten jedoch nicht mit sozialer Isolation oder Entfremdung in der Offline-Welt einher.Two studies dealing with the community quality of MUDs (Multi User Domains/Dungeons)—a special group of multiplayer-online-games—are reviewed. The first study focuses on the social identification of the MUD players with their respective MUDs and presents an analysis of the standardized questionnaire data from 217 MUD players and 110 non-players (UTZ 1999). The second study investigates social integration processes within three selected MUDs using participant observation, personal semi-structured interviews and standardized questionnaires with a sample of 40 experienced MUD players (GÖTZENBRUCKER 2001). The studies reveal that MUD-environments do create social cohesion and community both on the level of individual experience and social practice. Membership in virtual communities does not correlate with social isolation or estrangement in the offline-world

    Eingeladener Kommentar zum Beitrag "Face-to-face-Kommunikation und computervermittelte Kommunikation: Kritik eines Vergleichs" von Friederike Rothe

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    In einem Kommentar zu einem Beitrag von F. Rothe ĂŒber UnzulĂ€nglichkeiten der aktuellen Forschung zum Vergleich von Face-to-face-Kommunikation und computervermittelter Kommunikation (im gleichen Heft) wird zunĂ€chst auf die HeterogenitĂ€t der weltweiten Internet-Nutzung hingewiesen. Dann wird auf die Entwicklung der sozialwissenschaftlichen Internet-Forschung mit ihrer Vielfalt theoretischer und methodischer ZugĂ€nge eingegangen. Die als verzerrt angesehene Rekonstruktion der Online-Forschung im kommentierten Beitrag wird kritisiert. Abschließend werden Argumente gegen den Mythos einer entkörperlichten computervermittelten Kommunikation vorgetragen.The first part of the commentary refers to the heterogenity of Internet usage worldwide. The second section introduces the field of social scientific Internet research, stressing its multiple theoretical and methodological approaches. Part three criticizes the biased view of online research presented in the commented article. The fourth and final section argues against the myth of the disembodiment inherent in computer-mediated communication

    [Rezension von: Spetsmann-Kunkel, Martin, 1971-, Die Moral der Daytime Talkshow]

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    Die vorgelegte Monografie befasst sich aus soziologischer Sicht mit dem PhĂ€nomen der Daytime Talkshow. Der Autor stellt die verbreitete kulturpessimistische Kritik an dem TV-Format ("exhibitionistische GĂ€ste", "voyeuristische Zuschauer") in Frage. Er beschreibt zunĂ€chst die Merkmale des Formates und fasst Ergebnisse vorliegender Befragungsstudien zusammen, die eine Vielfalt von Teilnehmer- und Zuschauermotiven – jenseits der Pathologie – belegen. Unter RĂŒckgriff auf Konzepte wie Zivilisation und Individualisierung skizziert er mögliche gesellschaftliche Funktionen der Daytime Talkshow. Eine teilnehmende Redaktionsbeobachtung bei "Hans Meiser" sowie freie Interpretationen von drei Sendungen "Vera am Mittag" werden als "Empirie" prĂ€sentiert. Es mangelt der Arbeit leider an theoretischer und methodischer Stringenz sowie umfassender empirischer Fundierung. NĂŒtzlich ist sie, mit der EinschrĂ€nkung eines recht lĂŒckenhaften Literaturverzeichnisses, als engagierte, flĂŒssig lesbare EinfĂŒhrung in die Thematik.This book deals with the phenomenon of the daytime talk show from a sociological perspective. The author questions the common cultural pessimism of this TV format ("exhibitionist guests," "voyeuristic spectators"). He first describes the characteristics of the daytime talk show and summarizes the results of previous surveys that reveal a broad variety of talk show guests' and recipients' motives—beyond pathology. Drawing on concepts like civilization and individualisation, the book outlines the societal functions of the daytime talk show. A participatory observation study in the editorial office of "Hans Meiser" and free interpretations of three series from "Vera am Mittag" are presented as "empirical evidence." Unfortunately the book lacks theoretical and methodological rigor and a sound empirical basis. The bibliography could have been more comprehensive. The work is useful, though, as an inspired, readable introduction into the topic

    [Rezension von: Ben-ZeÊŸev, Aaron, 1949-, Love online]

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    Die Monografie von Aaron ZE'EV, Professor fĂŒr Philosophie und Kodirektor des Zentrums fĂŒr interdisziplinĂ€re Emotionsforschung an der UniversitĂ€t Haifa, hat sich zum Ziel gesetzt, die Besonderheiten von romantischer Liebe und sexuellem Begehren im Internet herauszuarbeiten. Der Autor versteht diese Thematik als einen Spezialfall seines Forschungsfeldes, nĂ€mlich der Untersuchung von Emotionen im Alltag. Online-Liebe und Cybersex werden theoretisch als ambivalente oder sogar paradoxe emotionale PhĂ€nomene konzeptualisiert. Insgesamt verortet ZE'EV computervermittelte zwischenmenschliche Interaktionen und Beziehungen in der Mitte zwischen reiner Phantasiewelt einerseits und herkömmlicher BeziehungsrealitĂ€t andererseits. Der Autor stellt keine eigenen PrimĂ€rdaten vor, sondern bezieht sich auf eine Reihe vorliegender empirischer Studien und arbeitet vor allem mit Zitaten aus Erfahrungsberichten und Leitfaden-Interviews. FĂŒr die Zukunft prognostiziert ZE'EV eine Zunahme erotischer und romantischer FlexibilitĂ€t durch niederschwellige Online-Erfahrungen, die zur Labilisierung der Ehe beitragen könnten. Interessant ist der ForschungsĂŒberblick aus philosophischer Perspektive mit dem BemĂŒhen um starke Systematisierung, welche jedoch teilweise in theoretisch und empirisch problematische Simplifizierungen fĂŒhrt.This monograph, by Aaron ZE'EV, Professor of Philosophy and Co-Director of the Centre for Interdisciplinary Research on Emotions at the University of Haifa, deals with the peculiarities of romantic love and sexual desire on the Internet. The author interprets the topic as a special case within his research area, namely the study of emotions in everyday life. Online love and cybersex are conceptualized as ambivalent, if not paradoxical, phenomena. According to ZE'EV, computer-mediated interpersonal interactions provide an intermediate area of experiencing that lies between solitary fantasy and social reality. The author does not present new data, but refers to a variety of published papers, mostly based on personal narratives and semi-structured interviews. Due to unrestrained online experiences, ZE'EV predicts an increase in erotic and romantic flexibility that might degrade the institution of marriage. The book presents a fruitful overview of research from a philosophical point of view. The author's effort to conceptually systemize the experience of online love and cybersex unfortunately sometimes leads to simplification
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