Book Reviews: Natural Language Processing for Social Media by Atefeh Farzindar and Diana Inkpen

Today, social media refers to a wide range of Web sites and Internet-based services that allow users to create content and interact with other users. Some of these tools, such as multi-party chats, discussion forums, blogs, and online reviews, have been a focus of natural language processing (NLP) research for quite some time now. But within the last decade, NLP work has expanded rapidly to cover an immense variety of new social media content—microblogs such as Twitter, social networks such as Facebook, comments on news articles, captions on user-contributed images such as on Flickr, and forums dedicated to specialized topics and needs (e.g., health and online education). Simultaneously, many other research communities are carrying out work using social media data—information science, information retrieval, network science, social media analytics, social science, psychology, and corpus linguistics. Today, a large number of businesses are also centered on, or benefit from, analytics performed on social media. Given these myriad research and commercial interests in the social media domain, we are at a time where we should seek to clearly understand what role NLP has in the field of social media analysis, both in terms of the key and interesting language questions, as well as contributions NLP can make to the research carried out in other fields. In this context, this short book by Farzindar and Inkpen is timely and exciting, filling an obvious gap.