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        <title>Sarcasm Detection : Building a Contextual Hierarchy</title>
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        <namePart type="given">Taradheesh</namePart>
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    <name type="personal">
        <namePart type="given">Navjyoti</namePart>
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            <namePart type="given">Malvina</namePart>
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        <name type="personal">
            <namePart type="given">Viviana</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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    <abstract>The conundrum of understanding and classifying sarcasm has been dealt with by the traditional theorists as an analysis of a sarcastic utterance and the ironic situation that surrounds it. The problem with such an approach is that it is too narrow, as it is unable to sufficiently utilize the two indispensable agents in making such an utterance, viz. the speaker and the listener. It undermines the necessary context required to comprehend a sarcastic utterance. In this paper, we propose a novel approach towards understanding sarcasm in terms of the existing knowledge hierarchy between the two participants, which forms the basis of the context that both agents share. The difference in relationship of the speaker of the sarcastic utterance and the disparate audience found on social media, such as Twitter, is also captured. We then apply our model on a corpus of tweets to achieve significant results and consequently, shed light on subjective nature of context, which is contingent on the relation between the speaker and the listener.</abstract>
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%0 Conference Proceedings
%T Sarcasm Detection : Building a Contextual Hierarchy
%A Bali, Taradheesh
%A Singh, Navjyoti
%Y Nissim, Malvina
%Y Patti, Viviana
%Y Plank, Barbara
%S Proceedings of the Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media (PEOPLES)
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F bali-singh-2016-sarcasm
%X The conundrum of understanding and classifying sarcasm has been dealt with by the traditional theorists as an analysis of a sarcastic utterance and the ironic situation that surrounds it. The problem with such an approach is that it is too narrow, as it is unable to sufficiently utilize the two indispensable agents in making such an utterance, viz. the speaker and the listener. It undermines the necessary context required to comprehend a sarcastic utterance. In this paper, we propose a novel approach towards understanding sarcasm in terms of the existing knowledge hierarchy between the two participants, which forms the basis of the context that both agents share. The difference in relationship of the speaker of the sarcastic utterance and the disparate audience found on social media, such as Twitter, is also captured. We then apply our model on a corpus of tweets to achieve significant results and consequently, shed light on subjective nature of context, which is contingent on the relation between the speaker and the listener.
%U https://aclanthology.org/W16-4313
%P 119-127

Markdown (Informal)

[Sarcasm Detection : Building a Contextual Hierarchy](https://aclanthology.org/W16-4313) (Bali & Singh, PEOPLES 2016)

• Sarcasm Detection : Building a Contextual Hierarchy (Bali & Singh, PEOPLES 2016)

ACL

• Taradheesh Bali and Navjyoti Singh. 2016. Sarcasm Detection : Building a Contextual Hierarchy. In Proceedings of the Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media (PEOPLES), pages 119–127, Osaka, Japan. The COLING 2016 Organizing Committee.