Affiliation:
1. Singapore Management University
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.
Publisher
Association for Computing Machinery (ACM)
Subject
General Computer Science,Management Information Systems
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