1,711 research outputs found
The impact of an emotionally expressive writing intervention on eating pathology in female students
© 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.Introduction: Previous research demonstrating emotional influences on eating and weight suggest that emotionally expressive writing may have a significant impact on reducing risk of eating pathology. This study examined the effects of writing about Intensely Positive Experiences on weight and disordered eating during a naturalistic stressor. Method: Seventy-one female students completed an expressive or a control writing task before a period of exams. Both groups were compared on BMI (kg/m2) and the Eating Disorder Examination – Questionnaire (EDE-Q) before the writing task and at 8-week follow-up. A number of secondary analyses were also examined (to identify potential mediators) including measures of attachment, social rank, self-criticism and self-reassurance, stress and mood. Results: There was a significant effect of intervention on changes in the subscales of the EDE-Q (p = .03). Specifically, expressive writers significantly reduced their dietary restraint while those in the control group did not. There was no significant effect of the intervention on changes in BMI or the other subscales of the EDE-Q (Eating, Weight and Shape Concern). There was also no effect of writing on any of the potential mediators in the secondary analyses. Discussion: Emotionally expressive writing may reduce the risk of dietary restraint in women but these findings should be accepted with caution. It is a simple and light touch intervention that has the potential to be widely applied. However, it remains for future research to replicate these results and to identify the mechanisms of action.Peer reviewedFinal Published versio
CAN LINGUISTIC ANALYSIS BE USED TO IDENTIFY WHETHER ADOLESCENTS WITH A CHRONIC ILLNESS ARE DEPRESSED?
Using Linguistic Features to Estimate Suicide Probability of Chinese Microblog Users
If people with high risk of suicide can be identified through social media
like microblog, it is possible to implement an active intervention system to
save their lives. Based on this motivation, the current study administered the
Suicide Probability Scale(SPS) to 1041 weibo users at Sina Weibo, which is a
leading microblog service provider in China. Two NLP (Natural Language
Processing) methods, the Chinese edition of Linguistic Inquiry and Word Count
(LIWC) lexicon and Latent Dirichlet Allocation (LDA), are used to extract
linguistic features from the Sina Weibo data. We trained predicting models by
machine learning algorithm based on these two types of features, to estimate
suicide probability based on linguistic features. The experiment results
indicate that LDA can find topics that relate to suicide probability, and
improve the performance of prediction. Our study adds value in prediction of
suicidal probability of social network users with their behaviors
Sensing Subjective Well-being from Social Media
Subjective Well-being(SWB), which refers to how people experience the quality
of their lives, is of great use to public policy-makers as well as economic,
sociological research, etc. Traditionally, the measurement of SWB relies on
time-consuming and costly self-report questionnaires. Nowadays, people are
motivated to share their experiences and feelings on social media, so we
propose to sense SWB from the vast user generated data on social media. By
utilizing 1785 users' social media data with SWB labels, we train machine
learning models that are able to "sense" individual SWB from users' social
media. Our model, which attains the state-by-art prediction accuracy, can then
be used to identify SWB of large population of social media users in time with
very low cost.Comment: 12 pages, 1 figures, 2 tables, 10th International Conference, AMT
2014, Warsaw, Poland, August 11-14, 2014. Proceeding
''Remembering'' World War II and willingness to fight : sociocultural factors in the social representation of historical warfare across 22 societies
Students from 22 nations answered a survey on the most important events in world history. At the national level, free recalling and a positive evaluation of World War II (WWII) were associated with World Values Survey willingness to fight for the country in a war and being a victorious nation. Willingness to fight, a more benign evaluation of WWII, and recall of WWII were associ- ated with nation-level scores on power distance and low postmaterialism, suggesting that values stressing obedience and competition between nations are associated with support for collective violence, whereas values of expressive individualism are negatively related. Internal political vio- lence was unrelated to willingness to fight, excluding direct learning as an explanation of legit- imization of violence. Recall of wars in general (operationalized by WWI recall) was also unrelated to willingness to fight. Results replicate and extend Archer and Gartner’s classic study showing the legitimization of violence by war to the domain of collective remembering
Semantic Sentiment Analysis of Twitter Data
Internet and the proliferation of smart mobile devices have changed the way
information is created, shared, and spreads, e.g., microblogs such as Twitter,
weblogs such as LiveJournal, social networks such as Facebook, and instant
messengers such as Skype and WhatsApp are now commonly used to share thoughts
and opinions about anything in the surrounding world. This has resulted in the
proliferation of social media content, thus creating new opportunities to study
public opinion at a scale that was never possible before. Naturally, this
abundance of data has quickly attracted business and research interest from
various fields including marketing, political science, and social studies,
among many others, which are interested in questions like these: Do people like
the new Apple Watch? Do Americans support ObamaCare? How do Scottish feel about
the Brexit? Answering these questions requires studying the sentiment of
opinions people express in social media, which has given rise to the fast
growth of the field of sentiment analysis in social media, with Twitter being
especially popular for research due to its scale, representativeness, variety
of topics discussed, as well as ease of public access to its messages. Here we
present an overview of work on sentiment analysis on Twitter.Comment: Microblog sentiment analysis; Twitter opinion mining; In the
Encyclopedia on Social Network Analysis and Mining (ESNAM), Second edition.
201
Breaking down the language of racism:a computerised linguistic analysis of racist groups’ self-defining online statements
The Internet represents a powerful tool for racist groups to build a sense of group consciousness and promote their cause. In the current study, we examined the language used by racist (n = 87), anti-racist (n = 50), and nonactivist (n = 1379) groups when describing their self-defining beliefs online. We used computerized linguistic analysis software to measure psychological indicators and antecedents of group consciousness and to examine the persuasive techniques used in online group communication. Racist and anti-racist groups were similar on some linguistic indicators of group consciousness (e.g., use of words reflecting perceived injustice), but differed on others (e.g., use of words reflecting group identification). Linguistic indicators of antecedents of group consciousness (moral foundations and focus on religion) differed across groups, with racist groups focused more on purity, respect for authority, and religion, and less on fairness than anti-racist groups. Racist groups also used less cognitively complex language than nonactivist groups (but similar levels to anti-racist groups). Our results contribute to understanding how racist groups promote their self-defining beliefs online, and identify several key factors that should be considered when designing policies to reduce racist groups' growth and impact
An Army of Me: Sockpuppets in Online Discussion Communities
In online discussion communities, users can interact and share information
and opinions on a wide variety of topics. However, some users may create
multiple identities, or sockpuppets, and engage in undesired behavior by
deceiving others or manipulating discussions. In this work, we study
sockpuppetry across nine discussion communities, and show that sockpuppets
differ from ordinary users in terms of their posting behavior, linguistic
traits, as well as social network structure. Sockpuppets tend to start fewer
discussions, write shorter posts, use more personal pronouns such as "I", and
have more clustered ego-networks. Further, pairs of sockpuppets controlled by
the same individual are more likely to interact on the same discussion at the
same time than pairs of ordinary users. Our analysis suggests a taxonomy of
deceptive behavior in discussion communities. Pairs of sockpuppets can vary in
their deceptiveness, i.e., whether they pretend to be different users, or their
supportiveness, i.e., if they support arguments of other sockpuppets controlled
by the same user. We apply these findings to a series of prediction tasks,
notably, to identify whether a pair of accounts belongs to the same underlying
user or not. Altogether, this work presents a data-driven view of deception in
online discussion communities and paves the way towards the automatic detection
of sockpuppets.Comment: 26th International World Wide Web conference 2017 (WWW 2017
The effects of poetry-writing SANTEL on erotic body image in remission of cancer in women: a pilot study
International audienceAbstract Aim: Our pilot study aims to describe the effects ofa new specific and structured protocol focused on poetic/erotic writing (named SANTEL) on the (re)sexualization ofbody image in women, who have experienced cancer.Procedure: The protocol consists of four steps: to choose alist of erotic verses focused on the body parts, to fill a semistructuredpoetic text, to write sentences after target phraseson the body; and in the end, to write a free poem. Mrs V.suffered from breast cancer, and one breast was removed.She and her husband participated in this poetic writing protocol,separately. We analyzed the linguistic metaphors ofthe body by QSR Nvivo10 software.Results: Using this protocol, we showed discourse variationsof metaphors before and after the experience of writing.Patient V used “I feel like an alien” as a starting metaphorto describe her cancer experience and after poetic writingsessions, she used other bodily metaphors like “My body isa flower” and “My sensual and white flesh”.Conclusion: This poetic perspective promises a type of“perceptive-literary surgery”, characterized by a sensualinvestment process after remission: a poetic reconstructionof erotic body image.Les effets d'un protocole d'écriture poétique SANTEL sur l'image érotique du corps dans le traitement du cancer féminin : étude pilote The effects of poetry-writing SANTEL on erotic body image in remission of cancer in women: a pilot study A. Santarpia · J. Tellène · M. Carrier Résumé Objectif : Cette étude pilote de type qualitative et exploratoire vise à décrire les effets d'un nouveau protocole d'écriture poético-érotique (nommée SANTEL) sur la rééro-tisation de l'image du corps chez une femme, ayant vécu un cancer. Matériel et méthodes : Il s'agit d'un protocole composé de quatre étapes : une liste des phrases à caractères poétiques et érotiques à choisir, un texte à trous à remplir, des amorces de phrases ciblées sur le corps et en fin un poème libre. Madame V. a subi un cancer du sein nécessitant une ablation complète. Madame V. et son conjoint exécutent le protocole d'écriture séparément. Nous montrons les variations discursives des métaphores utilisées avant et après l'expérience de l'écriture, à travers le logiciel d'analyse qualitative QSR NVivo10. Résultats : Madame V. passera de la métaphore initiale « je me sens une extraterrestre » vers la plus atténuée « Non. Je me dis qu'extraterrestre c'était peut-être un peu énorme ». En plus, elle utilisera de nouvelles métaphores linguistiques du corps pour raconter son image du corps telles que « ce corps de chair blanche » et « une fleur qui s'ouvre délicatement ». Conclusion : Cet exercice spécifique d'écriture promet un type de « chirurgie perceptive-littéraire » dans le processus d'investissement sensuel et affectif après la rémission, une reconstruction perceptive et poétique de l'image érotique du corps. Mots clés Métaphores perceptives · Image du corps · Cancer féminin · Corps érotique · Écriture poétique · Chirurgie perceptive-littéraire · Logiciel QSR NVivo10. Abstract Aim: Our pilot study aims to describe the effects of a new specific and structured protocol focused on poetic/ erotic writing (named SANTEL) on the (re)sexualization of body image in women, who have experienced cancer. Procedure: The protocol consists of four steps: to choose a list of erotic verses focused on the body parts, to fill a semi-structured poetic text, to write sentences after target phrases on the body; and in the end, to write a free poem. Mrs V. suffered from breast cancer, and one breast was removed. She and her husband participated in this poetic writing protocol , separately. We analyzed the linguistic metaphors of the body by QSR Nvivo10 software. Results: Using this protocol, we showed discourse variations of metaphors before and after the experience of writing. Patient V used " I feel like an alien " as a starting metaphor to describe her cancer experience and after poetic writing sessions, she used other bodily metaphors like " My body is a flower " and " My sensual and white flesh ". Conclusion: This poetic perspective promises a type of " perceptive-literary surgery " , characterized by a sensual investment process after remission: a poetic reconstruction of erotic body image. Keywords Bodily metaphors · Body image · Feminine cancer · Erotic body · Poetry writing · Perceptive-literary surgery · QSR Nvivo10 software
Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions
In online communities, antisocial behavior such as trolling disrupts
constructive discussion. While prior work suggests that trolling behavior is
confined to a vocal and antisocial minority, we demonstrate that ordinary
people can engage in such behavior as well. We propose two primary trigger
mechanisms: the individual's mood, and the surrounding context of a discussion
(e.g., exposure to prior trolling behavior). Through an experiment simulating
an online discussion, we find that both negative mood and seeing troll posts by
others significantly increases the probability of a user trolling, and together
double this probability. To support and extend these results, we study how
these same mechanisms play out in the wild via a data-driven, longitudinal
analysis of a large online news discussion community. This analysis reveals
temporal mood effects, and explores long range patterns of repeated exposure to
trolling. A predictive model of trolling behavior shows that mood and
discussion context together can explain trolling behavior better than an
individual's history of trolling. These results combine to suggest that
ordinary people can, under the right circumstances, behave like trolls.Comment: Best Paper Award at CSCW 201
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