NLP Applications—Social Media

Over the last decade, social media have been recognized as important sources of biomedical data generated directly by patients/consumers. With over 80% of the United States’ adult population using at least one social medium, these data sources have unprecedented reach. However, mining biomedical knowledge from social media data is not trivial due to the many challenges it poses. These include, but are not limited to, data size, noise, use of colloquial language, and ambiguity. Effective utilization of social media data for biomedical tasks requires the development of advanced natural language processing and machine learning methods. Continuing advances in natural language processing and machine learning research, coupled with the increased hardware capability for processing massive amounts of data have opened up high-utility opportunities. In this chapter, we present an overview of the relevance of social media data for biomedical research, the challenges it poses, natural language processing and machine learning strategies for effectively addressing these challenges, real-life applications of social media data, and current challenges and unsolved problems.