A web-based tool for collaborative social media data analysis

Abstract

User-generated content on social media sites such as Twitter and Facebook provides opportunity for researchers in various fields to understand human behaviors and social phenomena. On the one hand, these human behaviors and social phenomena are very complex in nature thus require in-depth qualitative analysis. On the other, the magnitude of social media data requires large-scale data analysis techniques. In this paper, we propose a web-based tool named SWAB (Social Web Analysis Buddy) that integrates both qualitative analysis and large-scale data mining techniques. Specifically, this tool supports asynchronous collaboration among researchers conducting inductive content analysis on textural data from users' online posts and conversations. It then aggregates the results and calculates the agreement among researchers, and builds modeling algorithms based on the qualitative results to classify large-scale social media text content. This current paper focuses on the overall workflow and user interface design of this tool. We demonstrate the prototype of this tool by analyzing studentposted content on Twitter. © 2013 IEEE.