Harbinger: An Analyzing and Predicting System for Online Social Network Users' Behavior

TL;DR

Harbinger is a system designed to analyze and predict user behavior in online social networks by visualizing activity patterns and building models to forecast future actions, aiding applications like tweet crawling and targeted advertising.

Contribution

The paper introduces Harbinger, a novel system that analyzes and predicts OSN user behavior through visualization and adjustable predictive models.

Findings

Effective visualization of user posting patterns.

Predictive models for user behavior with practical applications.

Potential for improved tweet crawling and targeted ads.

Abstract

Online Social Network (OSN) is one of the hottest innovations in the past years, and the active users are more than a billion. For OSN, users' behavior is one of the important factors to study. This demonstration proposal presents Harbinger, an analyzing and predicting system for OSN users' behavior. In Harbinger, we focus on tweets' timestamps (when users post or share messages), visualize users' post behavior as well as message retweet number and build adjustable models to predict users' behavior. Predictions of users' behavior can be performed with the discovered behavior models and the results can be applied to many applications such as tweet crawler and advertisement.