Natural Language Processing for Social Media

by Atefeh Farzindar, Diana Inkpen

In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on Natural Language Processing (NLP) tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, business intelligence, industry, marketing, and security and defense. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, and social networking.

166 pages, ebook

First published August 1, 2015

Reviews

[Zhijing Jin · Rating 5 out of 5]

Quite a fun read. It is interesting to see how NLP is used to analyze social media.

Example Social Media Applications:
- Healthcare
- Financial applications, e.g., predicting stock market trends
- Predicting voting intentions
- Media monitoring
- Security and defense applications
- Disaster response applications
- NLP-based user modeling
- Applications for entertainment
- Information visualization for social media

The part that interests me the most is social media's correlation with political events, although there are not many existing studies, and mostly on predicting election results published at NLP workshops.


The livelihood of NLP for social media is how the task is needed by real society, e.g., for government or institutional decisions, or to benefit individual's lives.
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More readings
- Handbook of computational social choice (Brandt, et al., 2016)