PHOAKS: a system for sharing recommendations
Communications of the ACM
Affective computing
Tracking point of view in narrative
Computational Linguistics
Major topic detection and its application to opinion summarization
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Wikinomics: How Mass Collaboration Changes Everything
Wikinomics: How Mass Collaboration Changes Everything
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
EmoHeart: conveying emotions in second life based on affect sensing from text
Advances in Human-Computer Interaction - Special issue on emotion-aware natural interaction
More than words: Social networks' text mining for consumer brand sentiments
Expert Systems with Applications: An International Journal
Negative online word-of-mouth: Behavioral indicator or emotional release?
Computers in Human Behavior
Potential Power and Problems in Sentiment Mining of Social Media
International Journal of Strategic Decision Sciences
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In this introduction, we present an overview of the current state of research in the Natural Language Processing tasks of subjectivity and sentiment analysis, as well as their application domains and closely-related research field of emotion detection. Although many definitions exist for these tasks and the research done within their frame spans over approaches with different objectives, we consider subjectivity analysis to deal with the detection of ''private states'' (opinions, emotions, sentiments, beliefs, speculations) and sentiment analysis as the task of detecting, extracting and classifying opinions and sentiments concerning different topics, as expressed in textual input. After describing the key concepts and research directions in these tasks, we present the main achievements obtained so far and the issues that remain to be tackled. Subsequently, we introduce each of the papers in this volume and present their contribution to the research areas of subjectivity and sentiment analysis. Finally, we conclude on the present state of work in these fields and reflect on the possible future developments.