Performance of System for Analyzing Diffusion of Social Media Messages in Real Time

Abstract

A social media message that is forwarded (e.g., Retweeted in Twitter) by many users may diffuse widely. Such a 'viral' message may have a major impact in the real world. If the content maligns a company, the company must respond as quickly as possible to defend its brand image. Timely knowledge about what kinds of information are diffusing in social media is thus quite important. We have developed a system that enables real-Time analysis of information diffusion in social media. We defined typical data access patterns and created a special view for complicated queries such as top-k ranking queries to improve query performance. The time window is customized by estimating diffusion extinction, which enables retention of diffusion data in the system as long as it is being retweeted frequently. Evaluation showed that the processing of simple access patterns was extremely fast, that the special view effectively improved performance, and that the time-window customization improved accuracy.