Mining User-Generated Content for Social Research and Other Applications

TL;DR: The main objective of this chapter is to present a general overview of the most relevant applications of text mining and natural language processing technologies evolving and emerging around the Web 2.0 phenomenon along with the main challenges and new research opportunities that are directly and indirectly derived from them.

Abstract: User-generated content is currently becoming a valuable means for sensing and measuring real world variables and parameters that are of interest to several actors in the society: politicians, government departments, security agencies, marketing researchers, service providers, etc. In response to this new scenario, large research efforts are being invested in the so-called “social media” phenomenon by a wide spectrum of institutions and organizations around the world, with many different objectives and a diverse scope of fields and disciplines. As a consequence, new technologies and applications are currently emerging on the grounds of human participation, interaction, and behavior on the Internet. The main objective of this chapter is to present a general overview of the most relevant applications of text mining and natural language processing technologies evolving and emerging around the Web 2.0 phenomenon (such as automatic categorization, document summarization, question answering, dialogue management, opinion mining, sentiment analysis, outlier identification, misbehavior detection, and social estimation and forecasting) along with the main challenges and new research opportunities that are directly and indirectly derived from them.