NDLI: Bandwagon Effect in Facebook Discussion Groups

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Bandwagon Effect in Facebook Discussion Groups

Content Provider	ACM Digital Library
Author	Wu, S. Felix Lai, Chun-Ming Wang, Keith C. Wang, Teng
Abstract	A core issue in online social networks is identifying content that will result in greater traffic and interaction. In this paper we use a large Facebook dataset and the concepts of bandwagon effect and information cascade from the field of communications to predict a post's life cycle without analyzing its content. Results from two models indicate evidence of (a) both factors being found on most discussion pages and (b) both factors having predictive power regarding the final number of participants in a post. To test for the bandwagon effect, we designed a system to predict article lifecycles, and found that for most Facebook pages, such predictions can be made within 30 minutes. We offer our data and analysis in support of a better understanding of the linkage between online social media research and journalism/information science theory, one that facilitates accurate predictions regarding posts that attract strong interest.
Starting Page	1
Ending Page	6
Page Count	6
File Format	PDF
ISBN	9781450337359
DOI	10.1145/2818869.2818914
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-10-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Social computing Data analytic Bandwagon effect Communication behavior Information cascade Online social network
Content Type	Text
Resource Type	Article

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