Sentiment Analysis

2. Auflage 2022
ISBN: 978-1-108-48637-8
Verlag: Cambridge University Press

Buch, Englisch, 448 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 837 g

Reihe: Studies in Natural Language Processing

Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and also new material on emotion and mood analysis techniques, emotion-enhanced dialogues, and multimodal emotion analysis.

Autoren/Hrsg.

Liu, Bing

Fachgebiete

• Sozialwissenschaften Soziologie | Soziale Arbeit Spezielle Soziologie Freizeitsoziologie, Konsumsoziologie, Alltagssoziologie, Populärkultur
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Sozialwissenschaften Psychologie Allgemeine Psychologie Kognitionspsychologie Emotion, Motivation, Handlung
• Sozialwissenschaften Politikwissenschaft Politische Kultur Politische Propaganda & Kampagnen, Politik & Medien
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Forschungsmethodik, Wissenschaftliche Ausstattung
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Marketing
• Geisteswissenschaften Sprachwissenschaft Computerlinguistik, Korpuslinguistik
• Mathematik | Informatik EDV | Informatik Informatik Natürliche Sprachen & Maschinelle Übersetzung
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Information Retrieval
• Sozialwissenschaften Medien- und Kommunikationswissenschaften Medienwissenschaften Medien & Gesellschaft, Medienwirkungsforschung
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

1. Introduction; 2. The Problem of Sentiment Analysis; 3. Document Sentiment Classification; 4. Sentence Subjectivity and Sentiment Classification; 5. Aspect Sentiment Classification; 6. Aspect and Entity Extraction; 7. Sentiment Lexicon Generation; 8. Analysis of Comparative Opinions; 9. Opinion Summarization and Search; 10. Analysis of Debates and Comments; 11. Mining Intents; 12. Detecting Fake or Deceptive Opinions; 13. Quality of Reviews; 14. Conclusions.

Über Autor(innen)

Liu, Bing
Bing Liu is a distinguished professor of Computer Science at the University of Illinois at Chicago. His current research interests include sentiment analysis, lifelong machine learning, natural language processing, and data mining. He has published extensively in top conferences and journals, and his research has been cited on the front page of the New York Times. Three of his research papers also received Test-of-Time awards. He is the recipient of ACM SIGKDD Innovation Award in 2018, and is a Fellow of the ACM, AAAI, and IEEE. He served as the Chair of ACM SIGKDD from 2013-2017.