Mining social media with social theories: a survey

Abstract

The increasing popularity of social media encourages more and more users to participate in various online activities and produces data in an unprecedented rate. Social media data is big, linked, noisy, highly unstructured and in- complete, and differs from data in traditional data mining, which cultivates a new research field - social media mining. Social theories from social sciences are helpful to explain social phenomena. The scale and properties of social media data are very different from these of data social sciences use to develop social theories. As a new type of social data, social media data has a fundamental question - can we apply social theories to social media data? Recent advances in computer science provide necessary computational tools and techniques for us to verify social theories on large-scale social media data. Social theories have been applied to mining social media. In this article, we review some key social theories in mining social media, their verification approaches, interesting findings, and state-of-the-art algorithms. We also discuss some future directions in this active area of mining social media with social theories.