| 000 | 03670cam a2200637Ii 4500 | ||
|---|---|---|---|
| 001 | on1123216889 | ||
| 003 | OCoLC | ||
| 005 | 20220711203147.0 | ||
| 006 | m o d | ||
| 007 | cr cnu|||unuuu | ||
| 008 | 191017s2019 enk ob 001 0 eng d | ||
| 040 |
_aDG1 _beng _erda _epn _cDG1 _dOCLCF _dUKMGB _dN$T _dRECBK _dUKAHL _dYDX _dOCLCQ _dOCLCO _dUMI |
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| 015 |
_aGBB9H7555 _2bnb |
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| 016 | 7 |
_a019591140 _2Uk |
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| 019 | _a1225940044 | ||
| 020 |
_a9781119671183 _q(electronic bk. ; _qoBook) |
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| 020 |
_a1119671183 _q(electronic bk. ; _qoBook) |
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| 020 |
_a9781119671220 _q(ePub ebook) |
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| 020 | _a1119671221 | ||
| 020 |
_a9781119671152 _q(electronic bk.) |
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| 020 |
_a1119671159 _q(electronic bk.) |
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| 020 |
_z9781786303998 _q(print) |
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| 024 | 7 |
_a10.1002/9781119671183 _2doi |
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| 029 | 1 |
_aAU@ _b000066234431 |
|
| 029 | 1 |
_aUKMGB _b019591140 |
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| 035 |
_a(OCoLC)1123216889 _z(OCoLC)1225940044 |
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| 037 |
_a9781119671220 _bWiley |
||
| 041 | 1 |
_aeng _hfre |
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| 050 | 4 | _aQA76.9.N38 | |
| 082 | 0 | 4 |
_a006.3/5 _223 |
| 049 | _aMAIN | ||
| 100 | 1 |
_aKaroui, Jihen, _eauthor. _94740 |
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| 245 | 1 | 0 |
_aAutomatic detection of irony : _bopinion mining in microblogs and social media / _cJihen Karoui, Farah Benamara, Véronique Moriceau. |
| 264 | 1 |
_aLondon, UK : _bISTE, Ltd. ; _aHoboken, NJ : _bWiley, _c2019. |
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| 300 | _a1 online resource | ||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 1 | _aCognitive science series | |
| 505 | 0 | _aFrom Opinion Analysis to Figurative Language Treatment -- Toward Automatic Detection of Figurative Language -- A Multilevel Scheme for Irony Annotation in Social Network Content -- Three Models for Automatic Irony Detection -- Towards a Multilingual System for Automatic Irony Detection -- Conclusion -- Categories of Irony Studied in Linguistic Literature. | |
| 504 | _aIncludes bibliographical references and index. | ||
| 588 | 0 | _aOnline resource; title from PDF title page (John Wiley, viewed October 17, 2019). | |
| 520 | _aIn 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). | ||
| 650 | 0 |
_aNatural language processing (Computer science) _94741 |
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| 650 | 0 |
_aData mining. _93907 |
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| 650 | 7 |
_aTECHNOLOGY & ENGINEERING _xElectronics _xGeneral. _2bisacsh _94742 |
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| 650 | 7 |
_aData mining. _2fast _0(OCoLC)fst00887946 _93907 |
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| 650 | 7 |
_aNatural language processing (Computer science) _2fast _0(OCoLC)fst01034365 _94741 |
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| 655 | 4 |
_aElectronic books. _93294 |
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| 700 | 1 |
_aBenamara, Farah, _eauthor. _94743 |
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| 700 | 1 |
_aMoriceau, Véronique, _eauthor. _94744 |
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| 830 | 0 |
_aCognitive science series. _94745 |
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| 856 | 4 | 0 |
_uhttps://doi.org/10.1002/9781119671183 _zWiley Online Library |
| 942 | _cEBK | ||
| 994 |
_aC0 _bDG1 |
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| 999 |
_c68331 _d68331 |
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