Parsing-based sarcasm sentiment recognition in Twitter data
Sentiment Analysis is a technique to identify people's opinion, attitude, sentiment, and emotion towards any specific target such as individuals, events, topics, product, organizations, services etc. Sarcasm is a special kind of sentiment that comprise of words which mean the opposite of what y...
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| Vydáno v: | 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) s. 1373 - 1380 |
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ACM
25.08.2015
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| Abstract | Sentiment Analysis is a technique to identify people's opinion, attitude, sentiment, and emotion towards any specific target such as individuals, events, topics, product, organizations, services etc. Sarcasm is a special kind of sentiment that comprise of words which mean the opposite of what you really want to say (especially in order to insult or wit someone, to show irritation, or to be funny). People often expressed it verbally through the use of heavy tonal stress and certain gestural clues like rolling of the eyes. These tonal and gestural clues are obviously not available for expressing sarcasm in text, making its detection reliant upon other factors. In this paper, two approaches to detect sarcasm in the text of Twitter data were proposed. The first is a parsing-based lexicon generation algorithm (PBLGA) and the second was to detect sarcasm based on the occurrence of the interjection word. The combination of two approaches is also shown and compared with the existing state-of-the-art approach to detect sarcasm. First approach attains a 0.89, 0.81 and 0.84 precision, recall and f - score respectively. Second approach attains 0.85, 0.96 and 0.90 precision, recall and f - score respectively in tweets with sarcastic hashtag. |
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| AbstractList | Sentiment Analysis is a technique to identify people's opinion, attitude, sentiment, and emotion towards any specific target such as individuals, events, topics, product, organizations, services etc. Sarcasm is a special kind of sentiment that comprise of words which mean the opposite of what you really want to say (especially in order to insult or wit someone, to show irritation, or to be funny). People often expressed it verbally through the use of heavy tonal stress and certain gestural clues like rolling of the eyes. These tonal and gestural clues are obviously not available for expressing sarcasm in text, making its detection reliant upon other factors. In this paper, two approaches to detect sarcasm in the text of Twitter data were proposed. The first is a parsing-based lexicon generation algorithm (PBLGA) and the second was to detect sarcasm based on the occurrence of the interjection word. The combination of two approaches is also shown and compared with the existing state-of-the-art approach to detect sarcasm. First approach attains a 0.89, 0.81 and 0.84 precision, recall and f - score respectively. Second approach attains 0.85, 0.96 and 0.90 precision, recall and f - score respectively in tweets with sarcastic hashtag. |
| Author | Babu, Korra Sathya Bharti, Santosh Kumar Jena, Sanjay Kumar |
| Author_xml | – sequence: 1 givenname: Santosh Kumar surname: Bharti fullname: Bharti, Santosh Kumar email: 513cs1037@nitrkl.ac.in organization: Comput. Sci. Eng., Nat. Inst. of Technol., Rourkela, India – sequence: 2 givenname: Korra Sathya surname: Babu fullname: Babu, Korra Sathya email: ksathyababu@nitrkl.ac.in organization: Comput. Sci. Eng., Nat. Inst. of Technol., Rourkela, India – sequence: 3 givenname: Sanjay Kumar surname: Jena fullname: Jena, Sanjay Kumar email: skjena@nitrkl.ac.in organization: Comput. Sci. Eng., Nat. Inst. of Technol., Rourkela, India |
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| Snippet | Sentiment Analysis is a technique to identify people's opinion, attitude, sentiment, and emotion towards any specific target such as individuals, events,... |
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| SubjectTerms | Feature extraction Media Meteorology Natural language processing Opinion mining Parsing Pragmatics Sarcasm Sentiment Tagging Tweets |
| Title | Parsing-based sarcasm sentiment recognition in Twitter data |
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