Social Media Mining with Natural Language Processing

Abstract

With the increasing role social media platforms like Facebook, Twitter, YouTube, and Tumbler play in our lives today, the body of data generated by their users continues to grow phenomenally. Accordingly, searches and processing of social media data beyond the limiting level of surface words are becoming increasingly important to business and governmental bodies, as well as to lay web users. Detection of sentiment, emotion, deception, gender, sarcasm, age, perspective, topic, community, and personality are all valuable social meaning components that promise to be important elements of next generation search engines and web intelligence. The emerging area of extracting social meaning from social media data using computational methods is known as Social Media Mining (SMM). This workshop is intended to first introduce the core ideas of natural language processing (NLP) and then to provide the ideas and some hands-on instruction in mining social data using NLP and machine learning technologies. As such, we will address practical issues related to building tools to mine social media data and some of the primary computational methods employed for modeling social meaning as occurring in these data.