A system to analyze Twitter data for social science study

摘要

Twitter data has been becoming more interesting in social science study since it can effectively reflect a nature of human behavior. Unfortunately, it is complicated to analyze Twitter data, and the existing tools are not suitable for this domain. In this paper, we present a system that is tailored to analyze Twitter data for the social science research. The system comprises four main functions including: (i) case study management, (ii) user/keyword search, (iii) interest group customization, and (iv) user-friendly analysis and visualization. Furthermore, three kinds of measures: connectivity, reciprocity, and mentioning, are presented to support the analysis process. Some of them are selectively employed from other domains, while others are invented in this work. The experiments were conducted on more than two millions Twitter activities related to the political situation in Thailand during May-June 2014. The results showed that our proposed measures can reveal useful knowledge in Twitter social group with the aid of the system that can provide scenario-based analysis and capture interactions among user groups.