sarcasm detection
Are Word Embedding based Features Useful for Sarcasm Detection?
... for sarcasm detection. We experiment with four past works in sarcasm detection, where we augment our word embedding-based features to their sets of fea- ...
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‘Who would have thought of that!’: A Hierarchical Topic Model for Extraction of Sarcasm prevalent Topics and Sarcasm Detection
... We presented a novel topic model that discovers sarcasm-prevalent topics. Our topic model uses a dataset of tweets (labeled as positive, negative and sarcastic), and estimates distributions corresponding to ...
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Sarcasm Detection in Chinese Using a Crowdsourced Corpus
... of sarcasm detection in texts involves not only linguistic knowledge represented in lexical, semantic-pragmatic, discourse levels, but also common-sense knowledge which is contextualized, situation-anchored ...
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Sarcasm Detection For Sentiment Analysis in Indonesian Tweets
... of sarcasm contained in a tweet sometimes causes incorrect determination of the tweet’s sentiment because sarcasm is difficult to analyze automatically, even by ...Hence, sarcasm detection ...
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A Multimodal Approach to Sarcasm Detection on Social Media
... and sarcasm. Emotion or sentiment detection requires more insights about the communication than it does for factual information ...retrieval. Sarcasm detection is particularly more difficult ...
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Modelling Context with User Embeddings for Sarcasm Detection in Social Media
... We introduce a deep neural network for automated sarcasm detection. Recent work has emphasized the need for mod- els to capitalize on contextual features, be- yond lexical and syntactic cues present in ...
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Towards Multimodal Sarcasm Detection (An Obviously Perfect Paper)
... Speech: Sarcasm detection in speech has mainly focused on the identification of prosodic cues in the form of acoustic patterns that are related to sarcastic ...of sarcasm (Bryant, 2010; Woodland and ...
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The effect of acute alcohol intoxication on the ability to detect sarcasm, and metacognitive judgements of sarcasm detection ability
... detect sarcasm an important aspect of ToM ...and sarcasm detection will be measured using Parts 2 and 3 of the ecologically validated The Awareness of Social Inference Test – Short Version (TASIT-S; ...
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A hybrid approach for Sarcasm Detection of Social Media Data
... The Contrast approach uses a logic i.e. a tweet having a positive sentiment and negative situations is considered to sarcastic and are marked as sarcastic. On the other hand Lexicon based approach consists of bag of ...
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Sarcasm Detection on Twitter using Feature-Based Approach
... of sarcasm makes the job even more ...commonly, sarcasm is expressed by positive sentimentthat is used in contrastwith the negative circumstance,for example a positive emotion, such as “love” or “happy”, ...
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Tweet Sarcasm Detection Using Deep Neural Network
... for sarcasm detection, neural models have seen increasing applications in sentiment analysis, which is a closely-related ...features. Sarcasm detection can benefit from such induction, and ...
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The Role of Conversation Context for Sarcasm Detection in Online Interactions
... casm/irony detection by looking at a particular type of context, conversation ...in sarcasm detection and (2) can we determine what part of the conversation context triggered the sarcastic ...of ...
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Harnessing Cognitive Features for Sarcasm Detection
... of sarcasm detection, with cogni- tive features extracted from eye-movement patterns of human ...readers. Sarcasm detec- tion has been a challenging research prob- lem, and its importance for NLP ...
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Magnets for Sarcasm: Making Sarcasm Detection Timely, Contextual and Very Personal
... stimuli, sarcasm detection in text has re- lied chiefly on the recognition of stock patterns and lexical ...cues. Sarcasm often highlights failed expectations by engaging in a pragmatic pretense that ...
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Putting Sarcasm Detection into Context: The Effects of Class Imbalance and Manual Labelling on Supervised Machine Classification of Twitter Conversations
... meaning. Sarcasm detection can therefore help improve natural language processing (NLP) ...modeled sarcasm detec- tion as classification, with two important limitations: ...when sarcasm is ...
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Harnessing Sequence Labeling for Sarcasm Detection in Dialogue from TV Series ‘Friends’
... views sarcasm detection in dialogue as a sequence labeling task, where a dialogue is made up of a se- quence of ...with sarcasm. Our goal is to predict sarcasm in each utterance, using ...
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A Survey of Sarcasm Detection in Social Media
... of sarcasm. Sarcasm is a sophisticated form of language use that acknowledges a gap between the intended meaning and the literal meaning of the ...ambiguity, sarcasm detection is a difficult ...
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Sarcasm Detection on Czech and English Twitter
... to sarcasm detection on Twitter in two lan- guages – English and ...in sarcasm detection in languages other than English ...at sarcasm detection in the Czech ...
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Harnessing Context Incongruity for Sarcasm Detection
... and sarcasm as a basis for sar- casm detection. Our sarcasm classifier uses four kinds of features: lexical, pragmatic, explicit in- congruity, and implicit incongruity ...
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SARCASM DETECTION AND SURVEYING USER AFFECTATION
... etc. Sarcasm is a special kind of sentiment that comprise of words which mean the opposite of what you really want to ...say. Sarcasm is a sort of sentiment where public expresses their negative emotions ...
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