1 Introduction to Social Media Analysis
1.2.1 Cross-language Document Analysis in Social Media Data
1.3 Challenges in Social Media Data
1.4 Semantic Analysis of Social Media
2 Linguistic Pre-processing of Social Media Texts
2.2 Generic Adaptation Techniques for NLP Tools
2.2.2 Re-training NLP Tools for Social Media Texts
2.7 Existing NLP Toolkits for English and Their Adaptation
2.8 Multi-linguality and Adaptation to Social Media Texts
3 Semantic Analysis of Social Media Texts
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
3.4.2 Emotion Analysis
3.4.3 Sarcasm Detection
3.4.4 Evaluation Measures for Opinion and Emotion Classification
3.5 Event and Topic Detection
3.5.1 Specified vs. Unspecified Event Detection
3.5.2 New vs. Retrospective Events
3.5.3 Emergency Situation Awareness
3.5.4 Evaluation Measures for Event Detection
3.6 Automatic Summarization
3.6.1 Update Summarization
3.6.2 Network Activity Summarization
3.6.3 Event Summarization
3.6.4 Opinion Summarization
3.6.5 Evaluation Measures for Summarization
3.7 Machine Translation
3.7.1 Adapting Phrase-based Machine Translation to Normalize Medical Terms
3.7.2 Translating Government Agencies’ Tweet Feeds
3.7.3 Hashtag Occurrence, Layout, and Translation
3.7.4 Machine Translation for Arabic Social Media
3.7.5 Evaluation Measures for Machine Translation
3.8 Summary
4 Applications of Social Media Text Analysis
4.1 Introduction
4.2 Healthcare Applications
4.3 Financial Applications
4.4 Predicting Voting Intentions
4.5 Media Monitoring
4.6 Security and Defense Applications
4.7
