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Semantic sentiment analysis in social streams
- 자료유형
- 전자책
- n993432979
- ISBN
- 9781614997511 (electronic bk.)
- ISBN
- 1614997519 (electronic bk.)
- ISBN
- 9781614997504 (print)
- 미국회청구기호
- QA76.5913
- DDC
- 006-23
- 소장사항
-
MAIN
- 저자명
- Saif, Hassan
- 서명/저자
- Semantic sentiment analysis in social streams / Hassan Saif
- 형태사항
- 1 online resource.
- 총서명
- Studies on the semantic web ; vol. 030
- 서지주기
- Includes bibliographical references.
- 내용주기
- 완전내용Title 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
- 내용주기
- 완전내용2.2.1.2 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
- 내용주기
- 완전내용3.3 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
- 내용주기
- 완전내용3.5 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
- 내용주기
- 완전내용4.3.2 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
- 일반주제명
- Social media
- 일반주제명
- COMPUTERS / General
- 일반주제명
- Semantic computing.
- 일반주제명
- Social media.
- 통일총서명
- Studies on the Semantic Web ; vol. 030.
- 전자적 위치 및 접속
- 링크정보보기
- Control Number
- yscl:140475
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