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Emotions in Online Gambling Communities: A Multilevel Sentiment Analysis

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Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis (HCII 2020)

Abstract

In this study, we analyzed whether interaction dynamics are related to emotional expressions within online gambling communities. As data, we used 8452 comments posted on Reddit gambling communities. The data were analyzed with sentiment analysis tool VADER and multilevel regression analysis. Results showed that comments were more positive when they were directed to other users and made by users with more interactive commenting behavior. Comments were less positive in those discussions that were most active and in those that mainly involved replies to other users. We also found that more positive posts received more positive commenting and negative posts received more negative comments. Overall, the activity and interactivity of communication and emotional correlation are associated with positive emotional expression in online communication. For negative emotions, we found evidence only for emotional correlation. Future studies should explore how interaction dynamics together with more contextual factors shape emotional expressions within online communities.

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References

  1. Mikal, J.P., Rice, R.E., Kent, R.G., Uchino, B.N.: 100 million strong: a case study of group identification and deindividuation on Imgur.com. New Media Soc. 18(11), 2485–2506 (2016)

    Article  Google Scholar 

  2. Keipi, T., Näsi, M.J., Oksanen, A., Räsänen, P.: Online Hate and Harmful Content: Cross-National Perspectives. Routledge, London (2017)

    Google Scholar 

  3. Robinson, C., Pond, R.: Do online support groups for grief benefit the bereaved? systematic review of the quantitative and qualitative literature. Comput. Hum. Behav. 100, 48–59 (2019)

    Article  Google Scholar 

  4. Mudry, T.E., Strong, T.: Doing recovery online. Qual. Health Res. 23(3), 313–325 (2013)

    Article  Google Scholar 

  5. Shim, M., Cappella, J.N., Han, J.Y.: How does insightful and emotional disclosure bring potential health benefits? study based on online support groups for women with breast cancer. J. Commun. 61(3), 432–454 (2011)

    Article  Google Scholar 

  6. Verberne, S., Batenburg, A., Sanders, R., Das, E., Lambooij, M.S.: Analyzing empowerment processes among cancer patients in an online community: A text mining approach. J. Med. Internet Res. 21(4), e9887 (2019)

    Google Scholar 

  7. Wang, Y.-C., Kraut, R.E., Levine, J.M.: Eliciting and receiving online support: using computer-aided content analysis to examine the dynamics of online social support. J. Med. Internet Res. 17(4), e99 (2015)

    Article  Google Scholar 

  8. Cole, D.A., Nick, E.A., Zelkowitz, R.L., Roeder, K.M., Spinelli, T.: Online social support for young people: does it recapitulate in-person social support; can it help? Comput. Hum. Behav. 68, 456–464 (2017)

    Article  Google Scholar 

  9. Cohen, S., Wills, T.A.: Stress, social support, and the buffering hypothesis. Psychol. Bull. 98(2), 310–357 (1985)

    Article  Google Scholar 

  10. Thoits, P.: Mechanisms linking social ties and support to physical and mental health. J. Health Soc. Behav. 52(2), 145–161 (2011)

    Article  Google Scholar 

  11. Minkkinen, J., Oksanen, A., Näsi, M., Keipi, T., Kaakinen, M., Räsänen, P.: Does social belonging to primary groups protect young people from the effects of pro-suicide sites? a comparative study of four countries. Crisis 37(1), 31–41 (2016)

    Article  Google Scholar 

  12. Kaakinen, M., Keipi, T., Räsänen, P., Oksanen, A.: Cybercrime victimization and subjective well-being: an examination of the buffering effect hypothesis among adolescents and young adults. Cyberpsychology Behav. Soc. Network. 21(2), 129–137 (2018)

    Article  Google Scholar 

  13. Kaakinen, M., Sirola, A., Savolainen, I., Oksanen, A.: Shared identity and shared information in social media: development and validation of the identity bubble reinforcement scale. Media Psychol. 23(1), 25–51 (2020)

    Article  Google Scholar 

  14. Kaakinen, M., Sirola, A., Savolainen, I., Oksanen, A.: Young people and gambling content in social media: an experimental insight. Drug and Alcohol Review, online first (2020)

    Google Scholar 

  15. Baele, S.J., Brace, L., Coan, TG.: From “Incel” to “Saint”: analyzing the violent worldview behind the 2018 Toronto attack. Terrorism and Political Violence, online first (2019)

    Google Scholar 

  16. Bliuc, A.-M., Betts, J., Vergani, M., Iqbal, M., Dunn, K.: Collective Identity Changes in Far-right Online Communities: The Role of Offline Intergroup Conflict. New Media Soc. 21(8), 1770–1786 (2019)

    Article  Google Scholar 

  17. Kaakinen, M., Räsänen, P., Näsi, M., Minkkinen, J., Keipi, T., Oksanen, A.: Social capital and online hate production: a four country survey. Crime, Law Soc. Change 69, 25–39 (2018)

    Article  Google Scholar 

  18. Borzekowski, D.L.G., Summer, S., Wilson, J.L., Peebles, R.: e-Ana and e-Mia: A Content Analysis of Pro-Eating Disorder Web Sites. Am. J. Public Health 100(8), 1526–1534 (2010)

    Article  Google Scholar 

  19. Oksanen, A., et al.: Pro-anorexia and anti-pro-anorexia videos on YouTube: sentiment analysis of user responses. J. Med. Internet Res. 17(11), e256 (2015)

    Article  Google Scholar 

  20. Sirola, A., Kaakinen, M., Turja, T., Oksanen, A.: (Un)doing deviance: social categorization in user reactions to proanorexia videos on YouTube. In: Digital technology: Advances in Research and Applications, pp. 231–261. Nova Science Publishers, New York (2019)

    Google Scholar 

  21. Savolainen, I., Sirola, A., Kaakinen, M., Oksanen, A.: Peer group identification as determinant of youth behavior and the role of perceived social support in problem gambling. J. Gambl. Stud. 35(1), 15–30 (2019)

    Article  Google Scholar 

  22. Sirola, A., Kaakinen, M., Oksanen, A.: Excessive gambling and online gambling communities. J. Gambl. Stud. 34(4), 1313–1325 (2018)

    Article  Google Scholar 

  23. O’Leary, K., Carroll, C.: The online poker sub-culture: Dialogues, interactions and networks. J. Gambl. Stud. 29(4), 613–630 (2013)

    Article  Google Scholar 

  24. Parke, A., Griffiths, M.D.: Poker gambling virtual communities: the use of Computer-Mediated Communication to develop cognitive poker gambling skills. Int. J. Cyber Behav. Psychol. Learn. (IJCBPL) 1(2), 31–44 (2011)

    Article  Google Scholar 

  25. Lyons, M., Aksayli, N.D., Brewer, G.: Mental distress and language use: Linguistic analysis of discussion forum posts. Comput. Hum. Behav. 87, 207–211 (2018)

    Article  Google Scholar 

  26. Rosenbusch, H., Evans, A.M., Zeelenberg, M.: Multilevel emotion transfer on YouTube: disentangling the effects of emotional contagion and homophily on video audiences. Soc. Psychol. Pers. Sci. 10(8), 1028–1035 (2019)

    Article  Google Scholar 

  27. Kramer, A.D.I., Guillory, J.E., Hancock, J.T.: Experimental evidence of massive-scale emotional contagion through social networks. Proc. Nat. Acad. Sci. 111, 8788–8790 (2014). https://doi.org/10.1073/pnas.1320040111

    Article  Google Scholar 

  28. Song, Y., Dai, X.-Y., Wang, J.: Not all emotions are created equal: expressive behavior of the networked public on China’s social media site. Comput. Hum. Behav. 60, 525–533 (2016)

    Article  Google Scholar 

  29. Himelboim, I., Cameron, K., Sweetser, K.D., Danelo, M., West, K.: Valence-based homophily on twitter: network analysis of emotions and political talk in the 2012 presidential election. New Media Soc. 18(7), 1382–1400 (2016)

    Article  Google Scholar 

  30. Gonzalez-Bailon, S., Kaltenbrunner, A., Banchs, R.E.: The structure of political discussion networks: A model for the analysis of online deliberation. J. Inf. Technol. 25(2), 230–243 (2010)

    Article  Google Scholar 

  31. Koudenburg, N., Postmes, T., Gordijn, E.H., Van Mourik Broekman, A.: Uniform and complementary social interaction: distinct pathways to solidarity. PLoS ONE 10(6), e0129061 (2015)

    Article  Google Scholar 

  32. Zhang, J., Danescu-Niculescu-Mizil, C., Sauper, C., Taylor, S.J.: Characterizing online public discussions through patterns of participant interactions. In: Proceedings of the ACM on Human-Computer Interaction 2(CSCW), p. 198 (2018)

    Google Scholar 

  33. Gray, S.L., Lockridge, L., Peleaux, R.: Social media, online communities, connection and coping: contextual considerations within the developmental period of emerging adulthood. In: Digital technology: Advances in Research and Applications, pp. 125–144. Nova Science Publishers, New York (2019)

    Google Scholar 

  34. Triggs, A.H., Møller, K., Neumayer, C.: Context collapse and anonymity among queer Reddit users. New Media Soc. Online first (2019)

    Google Scholar 

  35. Medvedev, A.N., Lambiotte, R., Delvenne, J.-C.: The anatomy of reddit: an overview of academic research. In: Ghanbarnejad, F., Saha Roy, R., Karimi, F., Delvenne, J.-C., Mitra, B. (eds.) DOOCN 2017. SPC, pp. 183–204. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-14683-2_9

    Chapter  Google Scholar 

  36. Bohrer, B.K., Foye, U., Jewell, T.: Recovery as a process: Exploring definitions of recovery in the context of eating-disorder-related social media forums. Int. J. Eating Disord. Online first (2020)

    Google Scholar 

  37. D’Agostino, A.R., Optican, A.R., Sowles, S.J., Krauss, M.J., Lee, K.E., Cavazos-Rehg, P.A.: Social networking online to recover from opioid use disorder: a study of community interactions. Drug Alcohol Depend. 181, 5–10 (2017)

    Article  Google Scholar 

  38. Hutto, C.J., Gilbert, E.: VADER: a parsimonious rule-based model for sentiment analysis of social media text. In: Proceedings of the 8th International Conference on Weblogs and Social Media, ICWSM 2014, pp. 216–225 (2014)

    Google Scholar 

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Acknowledgements

This study was funded by the Finnish Foundation for Alcohol Studies (Problem Gambling and Social Media Project, 2017–2019, PI: Atte Oksanen). David Garcia was funded by the Vienna Science and Technology Fund through the project “Emotional Well-Being in the Digital Society” (Grant No. VRG16-005).

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Correspondence to Markus Kaakinen .

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Kaakinen, M., Oksanen, A., Sirola, A., Savolainen, I., Garcia, D. (2020). Emotions in Online Gambling Communities: A Multilevel Sentiment Analysis. In: Meiselwitz, G. (eds) Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis. HCII 2020. Lecture Notes in Computer Science(), vol 12194. Springer, Cham. https://doi.org/10.1007/978-3-030-49570-1_38

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  • DOI: https://doi.org/10.1007/978-3-030-49570-1_38

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