Entropy-based Classification of 'Retweeting' Activity on Twitter

TL;DR

This paper introduces an entropy-based method to classify Twitter retweeting activities, effectively distinguishing between various user behaviors such as spam, news sharing, and promotional campaigns using only two features.

Contribution

It presents a novel, scalable, and robust information-theoretic approach for classifying Twitter retweeting activities based on time-interval and user entropy features.

Findings

Successfully categorized five distinct retweeting activities

Achieved high accuracy in activity separation using minimal features

Demonstrated method's robustness to sampling and missing data

Abstract

Twitter is used for a variety of reasons, including information dissemination, marketing, political organizing and to spread propaganda, spamming, promotion, conversations, and so on. Characterizing these activities and categorizing associated user generated content is a challenging task. We present a information-theoretic approach to classification of user activity on Twitter. We focus on tweets that contain embedded URLs and study their collective `retweeting' dynamics. We identify two features, time-interval and user entropy, which we use to classify retweeting activity. We achieve good separation of different activities using just these two features and are able to categorize content based on the collective user response it generates. We have identified five distinct categories of retweeting activity on Twitter: automatic/robotic activity, newsworthy information dissemination, advertising and promotion, campaigns, and parasitic advertisement. In the course of our investigations, we have shown how Twitter can be exploited for promotional and spam-like activities. The content-independent, entropy-based activity classification method is computationally efficient, scalable and robust to sampling and missing data. It has many applications, including automatic spam-detection, trend identification, trust management, user-modeling, social search and content classification on online social media.