Nothing Special   »   [go: up one dir, main page]

Skip to main content

How Does the Thread Level of a Comment Affect its Perceived Persuasiveness? A Reddit Study

  • Conference paper
  • First Online:
Intelligent Computing (SAI 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 507))

Included in the following conference series:

Abstract

Online interactions increasingly involve complex processes of persuasion and influence. Compared to the long history and richness of persuasion studies in traditional communication settings, we have limited understanding of how people are influenced by others in online communications and how persuasion works in online environments. While it is common in online discussions that some comments are threaded under a specific thread, it is un-known whether and how the thread level affects its perceived persuasiveness. To explore this research inquiry, we collected and analyzed threaded discussions in Reddit’s r/changemyview context. We found that the perceived persuasiveness of a comment fluctuates systematically from the top thread level to the most nested level. We conducted a semantic similarity analysis among adjacent comments in the threads examining how similar the comments are with respect to their content. Our results suggest that the first thread comment brings up a new idea or perspective, and the next comment matures it by adding new information to elaborate it, therefore, this comment is more likely to receive a delta point than the first comment. Additionally, this pattern continues onto the next comments. Implying that there is a common reasoning pattern in engaging in the threaded discussions in Reddit r/changemyview, our study sheds light on a comprehensive understanding of online participants’ reasoning behavior in threaded discussions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Bail, C.A.: Exposure to opposing views on social media can increase political polarization. Proc. Nat. Acad. Sci. 115(37), 9216–9221 (2018)

    Google Scholar 

  2. Xiao, L.: A message's persuasive features in Wikipedia's article for deletion discussions. In: Proceedings of the 9th International Conference on Social Media and Society, pp. 345–349 (2018)

    Google Scholar 

  3. Hidey, C., McKeown K.R.: Persuasive influence detection: the role of argument sequencing. In: Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), pp. 5173–5180 (2018)

    Google Scholar 

  4. Jo, Y., Poddar, S., Jeon, B., Shen, Q., Rosé, C.P., Neubig G.: Attentive interaction model: modeling changes in view in argumentation. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), vol. 1, pp. 103–116 (2018)

    Google Scholar 

  5. Tan, C., Niculae, V., Danescu-Niculescu-Mizil, C., Lee, L.: Winning arguments: interaction dynamics and persuasion strategies in good-faith online discussions. In: Proceedings of the 25th International Conference on World Wide Web (WWW), pp. 613–624 (2016)

    Google Scholar 

  6. Xiao, L., Khazaei, T.: Change others’ beliefs online: online comments’ persuasiveness. In: Proceedings of the 10th International Conference on Social Media and Society (2019)

    Google Scholar 

  7. Anand, P., et al.: Believe me—we can do this! Annotating persuasive acts in blog text. In: Proceedings of the 10th AAAI Conference on Computational Models of Natural Argument (AAAIWS 2011-10), pp. 11–15 (2011)

    Google Scholar 

  8. Cialdini, R.B.: Influence: The Psychology of Persuasion, pp. 173–174. Collins, New York (2007)

    Google Scholar 

  9. Marwell, G., Schmitt, D.R.: Dimensions of compliance-gaining behavior: an empirical analysis. Sociometry 350–364 (1967)

    Google Scholar 

  10. Walton, D., Reed, C., Macagno, F.: Argumentation Schemes. Cambridge University Press, Cambridge (2008)

    Google Scholar 

  11. Habernal, I., Gurevych, I.: Argumentation mining in user-generated web discourse. Comput. Linguist. 43(1), 125–179 (2017)

    Article  MathSciNet  Google Scholar 

  12. Hsieh, H.-P., Yan, R., Li, C.-T.: Will i win your favor? Predicting the success of altruistic requests. In: Bailey, J., Khan, L., Washio, T., Dobbie, G., Huang, J.Z., Wang, R. (eds.) PAKDD 2016. LNCS (LNAI), vol. 9651, pp. 177–188. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-31753-3_15

    Chapter  Google Scholar 

  13. Mitra, T., Gilbert, E.: The language that gets people to give: phrases that predict success on kickstarter. In: Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW), pp. 49–61 (2014)

    Google Scholar 

  14. Tausczik, Y.R., Pennebaker, J.W.: The psychological meaning of words: LIWC and computerized text analysis methods. J. Lang. Soc. Psychol. 29(1), 24–54 (2010)

    Article  Google Scholar 

  15. Iyer, R.R., Sycara, K.P., Li, Y.: Detecting type of persuasion: is there structure in persuasion tactics? In: Proceedings of the 17th Workshop on Computational Models of Natural Argument (CMNA) at International Conference on Artificial Intelligence and Law (ICAIL), pp. 54–64 (2017)

    Google Scholar 

  16. Guadagno, R.E., Cialdini, R.B.: Online persuasion: an examination of gender differences in computer-mediated interpersonal influence. Group Dyn. Theory Res. Pract. 6(1), 38 (2002)

    Article  Google Scholar 

  17. Price, V., Nir, L., Cappella, J.N.: Normative and informational influences in online political discussions. Commun. Theory 16(1), 47–74 (2006)

    Article  Google Scholar 

  18. Khazaei, T., Xiao, L., Mercer, R.: Writing to persuade: analysis and detection of persuasive discourse. In: Proceedings of iConference (2017). http://hdl.handle.net/2142/96673

  19. Hecking, T., Chounta, I.A., Hoppe, H.U.: Investigating social and semantic user roles in MOOC discussion forums. In: Proceedings of the Sixth International Conference on Learning Analytics & Knowledge (LAK), pp. 198–207 (2016)

    Google Scholar 

  20. Fan, Y.C., Wang, T.H., Wang, K.H.: Studying the effectiveness of an online argumentation model for improving undergraduate students’ argumentation ability. J. Comput. Assist. Learn. 36(4), 526–539 (2020)

    Article  Google Scholar 

  21. Cole, M.T., Swartz, L.B., Shelley, D.J.: Threaded discussion: the role it plays in e-learning. Int. J. Inf. Communicat. Technol. Educat. (IJICTE) 16(1), 16–29 (2020)

    Article  Google Scholar 

  22. Peterson, M.: Teaching the online marketing research course for MBA students. J. Market. Educat. 43, 371–385 (2021). 02734753211001422

    Google Scholar 

  23. Himelboim, I., Gleave, E., Smith, M.: Discussion catalysts in online political discussions: content importers and conversation starters. J. Comput. Mediat. Commun. 14(4), 771–789 (2009)

    Article  Google Scholar 

  24. Kang, J.H., Kim, J.: Analyzing answers in threaded discussions using a role-based information network. In: 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third International Conference on Social Computing, pp. 111–117 (2011)

    Google Scholar 

  25. Zhu, C., Rodríguez-Hidalgo, R.C.R.H., Questier, F., Torres-Alfonso, A.M.: Using social network analysis for analysing online threaded discussions. Int. J. Learn. Teach. Educat. Res. 10(3) (2015)

    Google Scholar 

  26. Samory, M., Cappelleri, V.M., Peserico, E.: Quotes reveal community structure and interaction dynamics. In: Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW), pp. 322–335 (2017)

    Google Scholar 

  27. Ishii, H.: TeamWorkStation: towards a seamless shared workspace. In: Proceedings of the 1990 ACM Conference on Computer-Supported Cooperative Work (CSCW), pp. 13–26 (1990)

    Google Scholar 

  28. Pinelle, D., Gutwin, C., Greenberg, S.: Task analysis for groupware usability evaluation: modeling shared workspace tasks with the mechanics of collaboration. ACM Trans. Comput. Hum. Interact. (TOCHI) 10(4), 281–311 (2003)

    Article  Google Scholar 

  29. Carroll, J.M., Rosson, M.B., Farooq, U., Xiao, L.: Beyond being aware. Inf. Organ. 19(3), 162–185 (2009)

    Article  Google Scholar 

  30. Scott, C.P., Wildman, J.L.: Culture, communication, and conflict: a review of the global virtual team literature. Lead. Global Teams 13–32 (2015)

    Google Scholar 

  31. Petty, R.E., Cacioppo, J.T.: The elaboration likelihood model of persuasion. In: Communication and Persuasion, pp. 1–24. Springer, New York (1986). https://doi.org/10.1007/978-1-4612-4964-1_1

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lu Xiao .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Xiao, L., Mensah, H. (2022). How Does the Thread Level of a Comment Affect its Perceived Persuasiveness? A Reddit Study. In: Arai, K. (eds) Intelligent Computing. SAI 2022. Lecture Notes in Networks and Systems, vol 507. Springer, Cham. https://doi.org/10.1007/978-3-031-10464-0_55

Download citation

Publish with us

Policies and ethics