Abstract
This article presents a systematic analysis of the patterns of behavior of individuals as well as groups observed in community-driven platforms for discussion like Reddit, where users usually exchange information and viewpoints on their topics of interest. We perform a statistical analysis of the behavior of posts and model the users’ interactions around them. A platform like Reddit which has grown exponentially, starting from a very small community to one of the largest social networks, with its large user base and popularity harboring a variety of behavior of users in terms of their activity. Our work provides interesting insights about a huge number of inactive posts which fail to attract attention despite their authors exhibiting Cyborg-like behavior to attract attention. We also observe short-lived yet extremely active posts emulate a phenomenon like Mayfly Buzz. A method is presented, to study the activity around posts which are highly active, to determine the presence of Limelight hogging activity. We also present a systematic analysis to study the presence of controversies in posts. We analyzed data from two periods of 1-year duration but separated by few years in time, to understand how social media has evolved through the years.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
C. Buntain, J. Golbeck, Identifying social roles in reddit using network structure, in Proceedings of the 23rd International Conference on World Wide Web (ACM, New York, 2014), pp. 615–620
Y. Choi, Y. Jung, S.H. Myaeng, Identifying controversial issues and their sub-topics in news articles, in Pacific-Asia Workshop on Intelligence and Security Informatics (Springer, Heidelberg, 2010), pp. 140–153
M.D. Conover, J. Ratkiewicz, M. Francisco, B. Gonçalves, F. Menczer, A. Flammini, Political polarization on twitter, in Fifth International AAAI Conference on Weblogs and Social Media (2011)
D. Gaffney, J.N. Matias, Caveat emptor, computational social science: large-scale missing data in a widely-published reddit corpus. PLoS One 13(7), e0200162 (2018)
K. Garimella, G.D.F. Morales, A. Gionis, M. Mathioudakis, Quantifying controversy on social media. Assoc. Comput. Mach. Trans. Soc. Comput. 1(1), 3 (2018)
M. Glenski, T. Weninger, Predicting user-interactions on reddit, in Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 (ACM, New York, 2017), pp. 609–612
M. Glenski, T. Weninger, Rating effects on social news posts and comments. Assoc. Comput. Mach. Trans. Intell. Syst. Technol. 8(6), 78 (2017)
M. Glenski, C. Pennycuff, T. Weninger, Consumers and curators: browsing and voting patterns on reddit. IEEE Trans. Comput. Soc. Syst. 4(4), 196–206 (2017)
K.I. Goh, A.L. Barabási, Burstiness and memory in complex systems. Europhys. Lett. 81(4), 48002 (2008)
V. Gómez, A. Kaltenbrunner, V. López, Statistical analysis of the social network and discussion threads in slashdot, in Proceeding 17th International Conference on World Wide Web (ACM, New York, 2008), pp. 645–654
H. Kwak, C. Lee, H. Park, S. Moon, What is twitter, a social network or a news media? in Proceeding 19th International Conference on World Wide Web (ACM, New York, 2010), pp. 591–600
D. Lazer, A. Pentland, L. Adamic, S. Aral, A.L. Barabási, D. Brewer, N. Christakis, N. Contractor, J. Fowler, M. Gutmann, T. Jebara, G. King, M. Macy, D. Roy, M. Van Alstyne, Computational social science. Science 323(5915), 721–723 (2009)
Y. Mejova, A.X. Zhang, N. Diakopoulos, C. Castillo, Controversy and Sentiment in Online News (2014). arXiv preprint: 1409.8152
R. Mills, Researching social new—is Reddit.com a mouthpiece for the ‘Hive Mind’, or a collective intelligence approach to information overload? in Proceedings of the Twelfth International Conference, the Social Impact of Social Computing ETHICOMP 2011 (Sheffield Hallam University, Sheffield, 2011), pp. 300–310
pushshift.io: databases. https://pushshift.io/resources/databases/ (2017). Accessed 01 Oct 2017
P. Singer, F. Flöck, C. Meinhart, E. Zeitfogel, M. Strohmaier, Evolution of reddit: from the front page of the internet to a self-referential community? in Proceedings of the 23rd International Conference on World Wide Web (ACM, New York, 2014), pp. 517–522
G. Stoddard, Popularity and quality in social news aggregators: a study of reddit and hacker news, in Proceedings of the 24th International Conference on World Wide Web (ACM, New York, 2015), pp. 815–818
S. Thukral, H. Meisheri, T. Kataria, A. Agarwal, I. Verma, A. Chatterjee, L. Dey, Analyzing behavioral trends in community driven discussion platforms like reddit, in 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (IEEE, Piscataway, 2018), pp. 662–669
S. Wasserman, K. Faust, Social Network Analysis: Methods and Applications, vol. 8 (Cambridge University, Cambridge, 1994)
T. Weninger, X.A. Zhu, J. Han, An exploration of discussion threads in social news sites: a case study of the Reddit community, in 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (IEEE, Piscataway, 2013), pp. 579–583
T. Yano, N.A. Smith, What’s worthy of comment? content and comment volume in political blogs, in ICWSM (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Thukral, S. et al. (2020). Characterizing Behavioral Trends in a Community Driven Discussion Platform. In: Kaya, M., Birinci, Ş., Kawash, J., Alhajj, R. (eds) Putting Social Media and Networking Data in Practice for Education, Planning, Prediction and Recommendation. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-33698-1_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-33698-1_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-33697-4
Online ISBN: 978-3-030-33698-1
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)