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Opinion Mining

Identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer's attitude towards a particular topic, product, etc. is positive, negative, or neutral (Source: Oxford Languages)

Image Source: Deep learning for sentiment analysis: A survey

Papers

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Showing 476–500 of 630 papers

TitleStatusHype
Product Feature Mining: Semantic Clues versus Syntactic Constituents—0
A Topic Model for Building Fine-grained Domain-specific Emotion Lexicon—0
Towards segment-based recognition of argumentation structure in short texts—0
Web Information Mining and Decision Support Platform for the Modern Service Industry—0
Aspect Based Sentiment Analysis to Extract Meticulous Opinion Value—0
Sentiment Analysis: A Survey—0
Hope and Fear: How Opinions Influence Factuality—0
Annotating the Focus of Negation in Japanese Text—0
Thematic Cohesion: measuring terms discriminatory power toward themes—0
Toward a unifying model for Opinion, Sentiment and Emotion information extraction—0
Meta-Classifiers Easily Improve Commercial Sentiment Detection Tools—0
Towards Shared Datasets for Normalization Research—0
Evaluation of different strategies for domain adaptation in opinion mining—0
Who cares about Sarcastic Tweets? Investigating the Impact of Sarcasm on Sentiment Analysis.—0
Investigating the Image of Entities in Social Media: Dataset Design and First Results—0
The NewSoMe Corpus: A Unifying Opinion Annotation Framework across Genres and in Multiple Languages—0
A Corpus of Comparisons in Product Reviews—0
A Large Corpus of Product Reviews in Portuguese: Tackling Out-Of-Vocabulary Words—0
Votter Corpus: A Corpus of Social Polling Language—0
The Dangerous Myth of the Star System—0
Benchmarking Twitter Sentiment Analysis Tools—0
Adapting a part-of-speech tagset to non-standard text: The case of STTS—0
Adapting Freely Available Resources to Build an Opinion Mining Pipeline in Portuguese—0
The USAGE review corpus for fine grained multi lingual opinion analysis—0
Corpus Annotation through Crowdsourcing: Towards Best Practice Guidelines—0
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