Automatic detection of irony : opinion mining in microblogs and social media /
In recent years, there has been a proliferation of opinion-heavy texts on the Web: opinions of Internet users, comments on social networks, etc. Automating the synthesis of opinions has become crucial to gaining an overview on a given topic. Current automatic systems perform well on classifying the...
| Main Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
London, UK : Hoboken, NJ :
ISTE, Ltd. ; Wiley,
2019.
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| Series: | Cognitive science series.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | In recent years, there has been a proliferation of opinion-heavy texts on the Web: opinions of Internet users, comments on social networks, etc. Automating the synthesis of opinions has become crucial to gaining an overview on a given topic. Current automatic systems perform well on classifying the subjective or objective character of a document. However, classifications obtained from polarity analysis remain inconclusive, due to the algorithms' inability to understand the subtleties of human language. Automatic Detection of Irony presents, in three stages, a supervised learning approach to predicting whether a tweet is ironic or not. The book begins by analyzing some everyday examples of irony and presenting a reference corpus. It then develops an automatic irony detection model for French tweets that exploits semantic traits and extralinguistic context. Finally, it presents a study of portability in a multilingual framework (Italian, English, Arabic). |
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| Physical Description: | 1 online resource |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781119671183 1119671183 9781119671220 1119671221 9781119671152 1119671159 |