Published on in Vol 17, No 11 (2015): November

Pro-Anorexia and Anti-Pro-Anorexia Videos on YouTube: Sentiment Analysis of User Responses

Pro-Anorexia and Anti-Pro-Anorexia Videos on YouTube: Sentiment Analysis of User Responses

Pro-Anorexia and Anti-Pro-Anorexia Videos on YouTube: Sentiment Analysis of User Responses

Journals

  1. Provoost S, Ruwaard J, van Breda W, Riper H, Bosse T. Validating Automated Sentiment Analysis of Online Cognitive Behavioral Therapy Patient Texts: An Exploratory Study. Frontiers in Psychology 2019;10 View
  2. Raitanen J, Oksanen A. Global Online Subculture Surrounding School Shootings. American Behavioral Scientist 2018;62(2):195 View
  3. Gomes R, Casais B. Feelings generated by threat appeals in social marketing: text and emoji analysis of user reactions to anorexia nervosa campaigns in social media. International Review on Public and Nonprofit Marketing 2018;15(4):591 View
  4. Hillyer G, MacLean S, Beauchemin M, Basch C, Schmitt K, Segall L, Kelsen M, Brogan F, Schwartz G. YouTube Videos as a Source of Information About Clinical Trials: Observational Study. JMIR Cancer 2018;4(1):e10060 View
  5. Park M. Information Sharing to Promote Risky Health Behavior on Social Media. Journal of Health Communication 2019;24(4):359 View
  6. Zunic A, Corcoran P, Spasic I. Sentiment Analysis in Health and Well-Being: Systematic Review. JMIR Medical Informatics 2020;8(1):e16023 View
  7. Livas C, Delli K, Pandis N. “My Invisalign experience”: content, metrics and comment sentiment analysis of the most popular patient testimonials on YouTube. Progress in Orthodontics 2018;19(1) View
  8. Park M. How Smoking Advocates are Connected Online: An Examination of Online Social Relationships Supporting Smoking Behaviors. Journal of Health Communication 2020;25(1):82 View
  9. Primack B, Escobar-Viera C. Social Media as It Interfaces with Psychosocial Development and Mental Illness in Transitional Age Youth. Child and Adolescent Psychiatric Clinics of North America 2017;26(2):217 View
  10. Rosenbusch H, Evans A, Zeelenberg M. Multilevel Emotion Transfer on YouTube: Disentangling the Effects of Emotional Contagion and Homophily on Video Audiences. Social Psychological and Personality Science 2019;10(8):1028 View
  11. Wang X, Parameswaran S, Bagul D, Kishore R. Can online social support be detrimental in stigmatized chronic diseases? A quadratic model of the effects of informational and emotional support on self-care behavior of HIV patients. Journal of the American Medical Informatics Association 2018;25(8):931 View
  12. Stock K. Mining location from social media: A systematic review. Computers, Environment and Urban Systems 2018;71:209 View
  13. Wang T, Mentzakis E, Brede M, Ianni A. Estimating Determinants of Attrition in Eating Disorder Communities on Twitter: An Instrumental Variables Approach. Journal of Medical Internet Research 2019;21(5):e10942 View
  14. Oksanen A, Näsi M, Minkkinen J, Keipi T, Kaakinen M, Räsänen P. Young people who access harm-advocating online content: A four-country survey. Cyberpsychology: Journal of Psychosocial Research on Cyberspace 2016;10(2) View
  15. Sirola A, Kaakinen M, Savolainen I, Oksanen A. Loneliness and online gambling-community participation of young social media users. Computers in Human Behavior 2019;95:136 View
  16. Veletsianos G, Kimmons R, Larsen R, Dousay T, Lowenthal P, Sugimoto C. Public comment sentiment on educational videos: Understanding the effects of presenter gender, video format, threading, and moderation on YouTube TED talk comments. PLOS ONE 2018;13(6):e0197331 View
  17. Strand M, Gustafsson S. Mukbang and Disordered Eating: A Netnographic Analysis of Online Eating Broadcasts. Culture, Medicine, and Psychiatry 2020;44(4):586 View
  18. Pinto J, Viana P, Nguyen N, Szczerbicki E, Trawiński B, Nguyen V. Improving Youtube video retrieval by integrating crowdsourced timed metadata. Journal of Intelligent & Fuzzy Systems 2019;37(6):7207 View
  19. Garitaonandia C, Karrera-Xuarros I, Jiménez-Iglesias E, Larrañaga N. Menores conectados y riesgos online: contenidos inadecuados, uso inapropiado de la información y uso excesivo de internet. El profesional de la información 2020 View
  20. Wang T, Brede M, Ianni A, Mentzakis E. Characterizing dynamic communication in online eating disorder communities: a multiplex network approach. Applied Network Science 2019;4(1) View
  21. Piryani R, Madhavi D, Singh V. Analytical mapping of opinion mining and sentiment analysis research during 2000–2015. Information Processing & Management 2017;53(1):122 View
  22. Bozkurt A, Aras I. Cleft Lip and Palate YouTube Videos: Content Usefulness and Sentiment Analysis. The Cleft Palate-Craniofacial Journal 2021;58(3):362 View
  23. Kaakinen M, Sirola A, Savolainen I, Oksanen A. Young people and gambling content in social media: An experimental insight. Drug and Alcohol Review 2020;39(2):152 View
  24. Wang T, Brede M, Ianni A, Mentzakis E, Tang M. Social interactions in online eating disorder communities: A network perspective. PLOS ONE 2018;13(7):e0200800 View
  25. DeJonckheere M, Nichols L, Vydiswaran V, Zhao X, Collins-Thompson K, Resnicow K, Chang T. Using Text Messaging, Social Media, and Interviews to Understand What Pregnant Youth Think About Weight Gain During Pregnancy. JMIR Formative Research 2019;3(2):e11397 View
  26. Jelodar H, Wang Y, Rabbani M, Ahmadi S, Boukela L, Zhao R, Larik R. A NLP framework based on meaningful latent-topic detection and sentiment analysis via fuzzy lattice reasoning on youtube comments. Multimedia Tools and Applications 2021;80(3):4155 View
  27. Holmes H, Lara A, Brown G. Social Media Use in College-age Youth: A Comprehensive Review and a Call to Action. Current Psychopharmacology 2020;9(2):128 View
  28. Chen N. Exploring the Cognitive and Emotional Impact of Online Climate Change Videos on Viewers. Sustainability 2020;12(22):9571 View
  29. Ventura V, Cavaliere A, Iannò B. #Socialfood: Virtuous or vicious? A systematic review. Trends in Food Science & Technology 2021;110:674 View
  30. Mansur A, Allamsyah Z, Amalia P. The Performance of Indonesia’s President: A Sentiment Analysis in Social Media. IOP Conference Series: Materials Science and Engineering 2021;1077(1):012004 View
  31. Pavan Kumar C, Dhinesh Babu L. Fuzzy based feature engineering architecture for sentiment analysis of medical discussion over online social networks. Journal of Intelligent & Fuzzy Systems 2021;40(6):11749 View

Books/Policy Documents

  1. Oksanen A, Miller B, Savolainen I, Sirola A, Demant J, Kaakinen M, Zych I. Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis. View
  2. Kaakinen M, Oksanen A, Sirola A, Savolainen I, Garcia D. Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis. View
  3. Hou J, Park M. Social Web and Health Research. View