Natural language processing for social media

• 作者： Farzindar, Atefeh.
• 其他作者：
  • Inkpen, Diana.
• 其他題名：
  • Synthesis lectures on human language technologies ;
• 出版： San Rafael, Calif. : Morgan & Claypool pub.
• 版本：Second edition
• 叢書名： Synthesis lectures on human language technologies,38
• 主題： Social media. , Natural language processing (Computer science) , Natural language processing (Computer science) , Social media.
• ISBN： 9781681736143 (hbk.): US$87.08 、 9781681736129 (pbk.) 、 1681736128 (pbk.) 、 1681736144 (hbk.)
• 資料類型: 圖書
• 內容註: Includes bibliographical references (p. 133-172) and index.
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• 摘要註: 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 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, healthcare, business intelligence, industry, marketing, and security and defence. 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, virtual reality, and social networking. In this second edition, we have added informat
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