Predicting participation in social media sites by analyzing user participation patterns

Liron Sivan, Barak Libai, Gal Oestreicher-Singer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The success of social media websites-Web 2.0 platforms that enable users to communicate among themselves-hinges on users' ability to generate content and respond to content supplied by others. Thus, understanding the current and expected patterns of participation among their users is a fundamental concern for the managers of social media websites. However, current prevailing prediction approaches use very simple benchmark models. We offer a novel approach for estimating the number of active users and predicting future participation. Using a unique data set from online forums, we demonstrate how probability models (specifically, the geometric/beta-Bernoulli model) traditionally used for customer loyalty analysis can be successfully used to assess participation patterns, and thus the future value of online communities. We further explore the factors that affect the usefulness of this approach. Compared with current methods, our approach generates better estimations of future visits as well as future contribution levels.

Original languageEnglish
Title of host publicationInternational Conference on Information Systems, ICIS 2012
Pages2460-2476
Number of pages17
StatePublished - 2012
EventInternational Conference on Information Systems, ICIS 2012 - Orlando, FL, United States
Duration: 16 Dec 201219 Dec 2012

Publication series

NameInternational Conference on Information Systems, ICIS 2012
Volume3

Conference

ConferenceInternational Conference on Information Systems, ICIS 2012
Country/TerritoryUnited States
CityOrlando, FL
Period16/12/1219/12/12

Keywords

  • E-business
  • Economics of information systems
  • Electronic commerce

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