Natural Language Processing for Social Media. Diana Inkpen

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СКАЧАТЬ as SemEval tasks), the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC), or the Conference and Labs of the Evaluation Forum (CLEF).

      In this third edition of the book, the authors added information about recent progress in NLP for social media applications, including more about the modern techniques provided by deep neural networks (DNNs) for modeling language and analyzing social media data.

       KEYWORDS

      social media, social networking, natural language processing, social computing, big data, semantic analysis, artificial intelligence, deep learning

      To my husband Massoud, and my daughters, Tina and Amanda, who are just about the best children a mom could hope for: happy, loving, and fun to be with.

       – Anna Atefeh Farzindar

      To my wonderful husband Nicu with whom I can climb any mountain, and to our sweet daughter Nicoleta.

       – Diana Inkpen

       Contents

       List of Figures

       List of Tables

       Preface

       Acknowledgments

       1 Introduction to Social Media Analysis

       1.1 Introduction

       1.2 Social Media Applications

       1.2.1 Cross-language Document Analysis in Social Media Data

       1.2.2 Deep Learning techniques for Social Media Data

       1.2.3 Real-world Applications

       1.3 Challenges in Social Media Data

       1.4 Semantic Analysis of Social Media

       1.5 Summary

       2 Linguistic Pre-processing of Social Media Texts

       2.1 Introduction

       2.2 Generic Adaptation Techniques for NLP Tools

       2.2.1 Text Normalization

       2.2.2 Re-training NLP Tools for Social Media Texts

       2.3 Tokenizers

       2.4 Part-of-speech Taggers

       2.5 Chunkers and Parsers

       2.6 Named Entity Recognizers

       2.7 Existing NLP Toolkits for English and Their Adaptation

       2.8 Multi-linguality and Adaptation to Social Media Texts

       2.8.1 Language Identification

       2.8.2 Dialect Identification

       2.9 Summary

       3 Semantic Analysis of Social Media Texts

       3.1 Introduction

       3.2 Geo-location Detection

       3.2.1 Mapping Social Media Information on Maps

       3.2.2 Readily Available Geo-location Information

       3.2.3 Geo-location based on Network Infrastructure

       3.2.4 Geo-location based on the Social Network Structure

       3.2.5 Content-based Location Detection

       3.2.6 Evaluation Measures for Geo-location Detection

       3.3 Entity Linking and Disambiguation

       3.3.1 Detecting Entities and Linked Data

       3.3.2 Evaluation Measures for Entity Linking

       3.4 Opinion Mining and Emotion Analysis

       3.4.1 Sentiment Analysis

       СКАЧАТЬ