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Semantic sentiment analysis in social streams
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| 자료유형 | 단행본 |
|---|---|
| 서명/저자사항 | Semantic sentiment analysis in social streams/ Hassan Saif. |
| 개인저자 | Saif, Hassan,author. |
| 형태사항 | 1 online resource. |
| 총서사항 | Studies on the semantic web;vol. 030 |
| ISBN | 9781614997511 1614997519 |
| 서지주기 | Includes bibliographical references. |
| 내용주기 | Title Page; Dedication; Statement; Abstract; Acknowledgements; Contents; List of Figures; List of Tables; 1 Introduction; 1.1 Motivation; 1.1.1 Sentiment Analysis of Twitter: Gaps and Challenges; 1.1.2 From Affect Words to Words' Semantics; 1.2 Research Questions, Hypotheses and Contributions; 1.3 Thesis Methodology and Outline; 1.4 Publications; Background; 2 Literature Review; 2.1 Background; 2.1.1 Fundamentals; 2.1.2 A Note on Terminology; 2.2 Sentiment Analysis of Twitter; 2.2.1 Traditional Sentiment Analysis Approaches; 2.2.1.1 The Machine Learning Approach 2.2.1.2 The Lexicon-based Approach2.2.1.3 The Hybrid Approach; 2.2.1.4 Discussion; 2.3 Semantic Sentiment Analysis; 2.3.1 Contextual Semantics; 2.3.2 Conceptual Semantics; 2.4 Summary and Discussion; 2.4.1 Discussion; Semantic Sentiment Analysis of Twitter; 3 Contextual Semantics for Sentiment Analysis of Twitter; 3.1 Introduction; 3.2 The SentiCircle Representation of Words' Semantics; 3.2.1 Overview; 3.2.2 SentiCircle Construction Pipeline; 3.2.2.1 Term Indexing; 3.2.2.2 Context Vector Generation; 3.2.2.3 SentiCircle Generation; 3.2.2.4 Senti-Median: The Overall Contextual Sentiment Value 3.3 SentiCircles for Sentiment Analysis3.3.1 Entity-level Sentiment Detection; 3.3.2 Tweet-level Sentiment Detection; 3.3.2.1 The Median Method; 3.3.2.2 The Pivot Method; 3.3.2.3 The Pivot-Hybrid Method; 3.3.3 Evaluation Setup; 3.3.3.1 Datasets; 3.3.3.2 Sentiment Lexicons; 3.3.3.3 Baselines; 3.3.3.4 Thresholds and Parameters Tuning; 3.3.4 Evaluation Results; 3.3.4.1 Entity-Level Sentiment Detection; 3.3.4.2 Tweet-Level Sentiment Detection; 3.3.4.3 Impact on Words' Sentiment; 3.4 SentiCircles for Adapting Sentiment Lexicons; 3.4.1 Evaluating SentiStrength on the Adapted Thelwall-Lexicon 3.5 Runtime Analysis3.6 Discussion; 3.7 Summary; 4 Conceptual Semantics for Sentiment Analysis of Twitter; 4.1 Introduction; 4.2 Conceptual Semantics for Supervised Sentiment Analysis; 4.2.1 Extracting Conceptual Semantics; 4.2.2 Conceptual Semantics Incorporation; 4.2.3 Evaluation Setup; 4.2.3.1 Datasets; 4.2.3.2 Semantic Concepts Extraction; 4.2.3.3 Baselines; 4.2.4 Evaluation Results; 4.2.4.1 Results on Incorporating Semantic Features; 4.2.4.2 Comparison of Results; 4.3 Conceptual Semantics for Lexicon-based Sentiment Analysis; 4.3.1 Enriching SentiCircles with Conceptual Semantics 4.3.2 Evaluation Results4.4 Discussion; 4.5 Summary; 5 Semantic Patterns for Sentiment Analysis of Twitter; 5.1 Introduction; 5.2 Related Work; 5.3 Semantic Sentiment Patterns of Words; 5.3.1 Syntactical Preprocessing; 5.3.2 Capturing Contextual Semantics and Sentiment of Words; 5.3.3 Extracting Patterns from SentiCircles; 5.4 Evaluation Setup; 5.4.1 Tweet-Level Evaluation Setup; 5.4.2 Entity-Level Evaluation Setup; 5.4.3 Evaluation Baselines; 5.4.4 Number of SS-Patterns in Data; 5.5 Evaluation Results; 5.5.1 Results of Tweet-Level Sentiment Classification |
| 일반주제명 | Semantic computing. Social media. COMPUTERS / General Semantic computing. Social media. |
| 언어 | 영어 |
| 바로가기 |  |
