Journal ArticleDOI
Verbal irony as implicit display of ironic environment: Distinguishing ironic utterances from nonirony☆
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TLDR
The authors proposed an implicit display theory of irony in order to provide a plausible explanation of how irony is distinguished from nonirony, which is consistent with the empirical findings from psycholinguistics.About:
This article is published in Journal of Pragmatics.The article was published on 2000-11-01. It has received 306 citations till now. The article focuses on the topics: Utterance & Irony.read more
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Sentiment Analysis and Opinion Mining
TL;DR: Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language as discussed by the authors and is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining.
Proceedings Article
Identifying Sarcasm in Twitter: A Closer Look
TL;DR: This work reports on a method for constructing a corpus of sarcastic Twitter messages in which determination of the sarcasm of each message has been made by its author and uses this reliable corpus to compare sarcastic utterances in Twitter to utterances that express positive or negative attitudes without sarcasm.
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Sentiment Analysis: Mining Opinions, Sentiments, and Emotions
TL;DR: Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes as discussed by the authors, which offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis.
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Book Review: Sentiment Analysis: Mining Opinions, Sentiments, and Emotions by Bing Liu
TL;DR: This comprehensive introduction to sentiment analysis 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.
Proceedings Article
Semi-supervised recognition of sarcastic sentences in Twitter and Amazon
TL;DR: This paper experiments with semi-supervised sarcasm identification on two very different data sets: a collection of 5.9 million tweets collected from Twitter, and aCollection of 66000 product reviews from Amazon.
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Politeness : Some Universals in Language Usage
TL;DR: Gumperz as discussed by the authors discusses politeness strategies in language and their implications for language studies, including sociological implications and implications for social sciences. But he does not discuss the relationship between politeness and language.
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Politeness: Some Universals in Language Usage
TL;DR: This paper presents an argument about the nature of the model and its implications for language studies and Sociological implications and discusses the role of politeness strategies in language.
Journal ArticleDOI
Women, Fire, and Dangerous Things: What Categories Reveal about the Mind
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Relevance: Communication and Cognition
Dan Sperber,Deirdre Wilson +1 more
TL;DR: In this paper, the authors present a list of symbols for verb-verb communication in the context of Verbal Communication, including the following: preface to second edition, preface and postface to first edition.