Publication Type

Journal Article

Version

acceptedVersion

Publication Date

2012

Abstract

Real-time microblogging systems such as Twitter offer users an easy and lightweight means to exchange information. Instead of writing formal and lengthy messages, microbloggers prefer to frequently broadcast several short messages to be read by other users. Only when messages are interesting, are they propagated further by the readers. In this article, we examine user behavior relevant to information propagation through microblogging. We specifically use retweeting activities among Twitter users to define and model originating and promoting behavior. We propose a basic model for measuring the two behaviors, a mutual dependency model, which considers the mutual relationships between the two behaviors, and a range-based model, which considers the depth and reach of users’ original tweets. Next, we compare the three behavior models and contrast them with the existing work on modeling influential Twitter users. Last, to demonstrate their applicability, we further employ the behavior models to detect interesting events from sudden changes in aggregated information propagation behavior of Twitter users. The results will show that the proposed behavior models can be effectively applied to detect interesting events in the Twitter stream, compared to the baseline tweet-based approaches.

Keywords

Twitter, Retweet, Weak retweet, Behavior modeling, Originating behavior, Promoting behavior, Information propagation, Event detection

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Publication

ACM Transactions on Management Information Systems

Volume

3

Issue

3

First Page

1

Last Page

30

ISSN

2158-656X

Identifier

10.1145/2361256.2361258

Publisher

ACM

Additional URL

http://doi.org/10.1145/2361256.2361258

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