Title :
Retention in Online Blogging: A Case Study of the Blogster Community
Author :
Kayes, Imrul ; Chakareski, Jacob
Author_Institution :
Department of Computer Science and Engineering, University of South Florida, Tampa, FL, USA
fDate :
3/1/2015 12:00:00 AM
Abstract :
Community-based blogging platforms can be rich sources of information on a variety of specialized topics, from finance to parenting. The usefulness of such platforms depends heavily on user participation and contribution. However, one potential problem is lower retention: users’ fail to contribute in the long run. This paper is an investigation of retention in the popular community blogging platform “Blogster.” We use the points users earn for their activities as a proxy of retention and explore the attributes that are associated with their retention. We find that highly retained users are most central in the network and their blogger friends are mutually less connected. They get more views and comments to their posted blogs. We also examine the homophily of retention in the social network. Based on our empirical observations, we build a classifier that is able to detect top retained users with accuracy as high as 94%. Our work has theoretical implications for the social behavior literature of community bloggers and practical design implications for potential community blogging platform developers.
Keywords :
Accuracy; Blogs; Crawlers; Internet; Predictive models; Social network services; Terrorism; Bloggers; community blogging; retention;
Journal_Title :
Computational Social Systems, IEEE Transactions on
DOI :
10.1109/TCSS.2015.2495135