Learning to Predict with Highly Granular Temporal Data: Estimating individual behavioral profiles with smart meter data

Big spatio-temporal datasets, available through both open and administrative data sources, offer significant potential for social science research. The magnitude of the data allows for increased resolution and analysis at individual level. While there are recent advances in forecasting techniques for highly granular temporal data, little attention is given to segmenting the time series and finding homogeneous patterns. In this paper, it is proposed to estimate behavioral profiles of individuals' activities over time using Gaussian Process-based models. In particular, the aim is to investigate how individuals or groups may be clustered according to the model parameters. Such a Bayesian non-parametric method is then tested by looking at the predictability of the segments using a combination of models to fit different parts of the temporal profiles. Model validity is then tested on a set of holdout data. The dataset consists of half hourly energy consumption records from smart meters from more than 100,000 households in the UK and covers the period from 2015 to 2016. The methodological approach developed in the paper may be easily applied to datasets of similar structure and granularity, for example social media data, and may lead to improved accuracy in the prediction of social dynamics and behavior

¿Cómo usan los parlamentos las redes sociales? Un estudio comparado y longitudinal aplicado a países de América y Europa (2010, 2015 y 2017)

Introducción: El artículo analiza el uso que los parlamentos hacen de las redes sociales a partir del estudio de las cámaras representativas de Argentina, Chile, Colombia, Ecuador, Estados Unidos, España, Francia, Italia, Reino Unido y Suecia. Metodología: A través de un análisis de contenido efectuado en 2010, 2015 y 2017, el texto presenta la evolución y la trayectoria del uso de las redes sociales en cada uno de los años y países de estudio. Resultados y conclusiones: Los resultados indican un aumento del uso informativo y divulgativo de las redes sociales en los parlamentos, pero demuestra pocos avances en la creación de espacios deliberativos o participativos en las plataformas. El artículo identifica acciones parlamentarias orientadas a integrar el ecosistema mediático cambiante, ligado a las redes sociales, aunque la intención se limita a la figuración y al impacto dentro del marco mediático, más que en la promoción de la participación mediada por las redes sociales.Introduction: The article analyses how parliaments use social media through the study of the representative chambers of Argentina, Chile, Colombia, Ecuador, United States, Spain, France, Italy, United Kingdom and Sweden. Methodology: Using a content analysis method developed in 2010, 2015 and 2017, the text presents the evolution and the paths of the social media use of the selected parliaments. Results and conclusions: Results show a progression in the informative parliamentary use of social media, but they highlight few advances in the creation of deliberative or participative arenas in social platforms. The paper identifies parliamentary actions oriented to integrate the changing media ecosystem, linked to social media, but the institutional intention is limited to the presence and the impact inside the media framework, more than in the promotion of the social media mediated participation

Alcohol Portrayals on Social Media (Social Media)

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: Durchführung 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 für Prävention? [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). Picture me drinking: Alcohol-related posts by Instagram influencers popular among adolescents and young adults. Frontiers in Psychology, 10, 2991. https://doi.org/10.3389/fpsyg.2019.02991 Mayrhofer, M., & Naderer, B. (2019). Mass media as alcohol educator for everyone? Effects of portrayed alcohol consequences and the influence of viewers’ characteristics. Media Psychology, 22(2), 217–243. https://doi.org/10.1080/15213269.2017.1378112 Moreno, M. A., Briner, L. R., Williams, A., Brockman, L., Walker, L., & Christakis, D. A. (2010). A content analysis of displayed alcohol references on a social networking web site. The Journal of Adolescent Health: Official Publication of the Society for Adolescent Medicine, 47(2), 168–175. https://doi.org/10.1016/j.jadohealth.2010.01.001 Moreno, M. A., D’Angelo, J., & Whitehill, J. (2016). Social media and alcohol: Summary of research, intervention ideas and future study directions. Media and Communication, 4(3), 50–59. https://doi.org/10.17645/mac.v4i3.529 Noel, J. K. (2021). Using social media comments to reduce alcohol purchase intentions: An online experiment. Drug and Alcohol Review, 40(6), 1047–1055. https://doi.org/10.1111/dar.13262 Ricard, B. J., & Hassanpour, S. (2021). Deep learning for identification of alcohol-related content on social media (Reddit and Twitter): Exploratory analysis of alcohol-related outcomes. Journal of Medical Internet Research, 23(9), e27314. https://doi.org/10.2196/27314 Russell, A. M., Davis, R. E., Ortega, J. M., Colditz, J. B., Primack, B., & Barry, A. E. (2021). #Alcohol: Portrayals of alcohol in top videos on TikTok. Journal of Studies on Alcohol and Drugs, 82(5), 615–622. https://doi.org/10.15288/jsad.2021.82.615 Stautz, K., Brown, K. G., King, S. E., Shemilt, I., & Marteau, T. M. (2016). Immediate effects of alcohol marketing communications and media portrayals on consumption and cognition: A systematic review and meta-analysis of experimental studies. BMC Public Health, 16, 465. https://doi.org/10.1186/s12889-016-3116-8 Strowger, M., & Braitman, A. L. (2022). Using social network methodology to examine the effects of exposure to alcohol-related social media content on alcohol use: A critical review. Experimental and Clinical Psychopharmacology. Advance online publication. https://doi.org/10.1037/pha0000561 Tamersoy, A., Choudhury, M. de, & Chau, D. H. (2015). Characterizing smoking and drinking abstinence from social media. HT '15: The Proceedings of the 26th ACM Conference on Hypertext and Social Media, 2015, 139–148. https://doi.org/10.1145/2700171.2791247 Turnwald, B. P., Anderson, K. G., Markus, H. R., & Crum, A. J. (2022). Nutritional analysis of foods and beverages posted in social media accounts of highly followed celebrities. JAMA Network Open, 5(1), e2143087. https://doi.org/10.1001/jamanetworkopen.2021.43087 Van den Bulck, H., Simons, N., & van Gorp, B. (2008). Let's drink and be merry: The framing of alcohol in the prime-time American youth series The OC. Journal of Studies on Alcohol and Drugs, 69(6), 933–940. https://doi.org/10.15288/jsad.2008.69.933 Westgate, E. C., & Holliday, J. (2016). Identity, influence, and intervention: The roles of social media in alcohol use. Current Opinion in Psychology, 9, 27–32. https://doi.org/10.1016/j.copsyc.2015.10.014 World Health Organization Regional Office for Europe (WHO). (2020). Alcohol marketing in the WHO European Region: update report on the evidence and recommended policy actions. https://apps.who.int/iris/bitstream/handle/10665/336178/WHO-EURO-2020-1266-41016-55678-eng.pdf?sequence=1&isAllowed=

Content marketing model for leading web content management

This paper is envisaged to provide the Ukrainian businesses with suggestions for a content marketing model for the effective management of website content in order to ensure its leading position on the European and world markets. Our study employed qualitative data collection with semi-structured interviews, survey, observation methods, quantitative and qualitative methods of content analysis of regional B2B companies, as well as the comparative analysis. The following essential stages of the content marketing process as preliminary search and analysis, website content creation, promotion and distribution, and content marketing progress assessment were identified and classified in detail. The strategic decisions and activities at each stage of the process showed how a company’s on-site and off-site content can be used as a tool to establish the relationship between the brand and its target audience and increase brand visibility online. This study offered several useful insights into how website content, social media and various optimization techniques work together in engaging with the target audience and driving website traffic and sales leads. We constructed and described the content marketing model elaborated for effective web content management that can be useful for those companies that start to consider employing content marketing strategy for achieving business goals and increasing a leadership position

The serialized past: archaeology news online

Maintaining the public’s interest in the past has long been a major concern among archaeologists, and practitioners since Mortimer Wheeler have appreciated the value of reporting their finds through mass media outlets (Moshenska and Schadla-Hall 2011). While teaching the honors module Archaeology in Contemporary Society at the University of Chester in 2015, I wanted to assess the portrayal of our discipline in the news. I put together a computer lab session that collated headlines into word clouds and found some peculiarities of reporting across news sources. Yet when it came time to producing essays, few students chose to write about this subject. While there have been some great studies of archaeology in the media, they are aging fast and new work has yet to catch up with the digital world of online news

360 Quantified Self

Wearable devices with a wide range of sensors have contributed to the rise of the Quantified Self movement, where individuals log everything ranging from the number of steps they have taken, to their heart rate, to their sleeping patterns. Sensors do not, however, typically sense the social and ambient environment of the users, such as general life style attributes or information about their social network. This means that the users themselves, and the medical practitioners, privy to the wearable sensor data, only have a narrow view of the individual, limited mainly to certain aspects of their physical condition. In this paper we describe a number of use cases for how social media can be used to complement the check-up data and those from sensors to gain a more holistic view on individuals' health, a perspective we call the 360 Quantified Self. Health-related information can be obtained from sources as diverse as food photo sharing, location check-ins, or profile pictures. Additionally, information from a person's ego network can shed light on the social dimension of wellbeing which is widely acknowledged to be of utmost importance, even though they are currently rarely used for medical diagnosis. We articulate a long-term vision describing the desirable list of technical advances and variety of data to achieve an integrated system encompassing Electronic Health Records (EHR), data from wearable devices, alongside information derived from social media data.Comment: QCRI Technical Repor