Building and evaluating resources for sentiment analysis in the Greek language.
Sentiment lexicons and word embeddings constitute well-established sources of information for sentiment analysis in online social media. Although their effectiveness has been demonstrated in state-of-the-art sentiment analysis and related tasks in the English language, such publicly available resour...
| Publicado en: | Language Resources & Evaluation Vol. 52; no. 4; pp. 1021 - 1045 |
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| Autores principales: | , , , , , , , |
| Formato: | Artículo |
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Springer Nature
Dec2018
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=132695161&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 132695161 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Dec2018 vid: 52 iid: 4 pid: 237 pub: Springer Nature artinfo: ui: 132695161 10.1007/s10579-018-9420-4 ppf: 1021 ppct: 24 formats: fmt: – @attributes: type: T – @attributes: type: P size: 740KB tig: atl: Building and evaluating resources for sentiment analysis in the Greek language. aug: au: Tsakalidis, Adam Papadopoulos, Symeon Voskaki, Rania Ioannidou, Kyriaki Boididou, Christina Cristea, Alexandra I. Liakata, Maria Kompatsiaris, Yiannis affil: Department of Computer Science, University of Warwick, Coventry, UK The Alan Turing Institute, London, UK Information Technologies Institute, CERTH, Thessaloníki, Greece Centre for the Greek Language, Thessaloníki, Greece Laboratory of Translation and Natural Language Processing, Aristotle University of Thessaloniki, Thessaloníki, Greece Department of Computer Science, University of Durham, Durham, UK su: Sentiment analysis Greek language Computational linguistics English language Lexicon sug: subj: Sentiment analysis Greek language Computational linguistics English language Lexicon keyword: Emotion analysis Natural language processing Opinion mining Sarcasm detection Sentiment lexicon Word embeddings ab: Sentiment lexicons and word embeddings constitute well-established sources of information for sentiment analysis in online social media. Although their effectiveness has been demonstrated in state-of-the-art sentiment analysis and related tasks in the English language, such publicly available resources are much less developed and evaluated for the Greek language. In this paper, we tackle the problems arising when analyzing text in such an under-resourced language. We present and make publicly available a rich set of such resources, ranging from a manually annotated lexicon, to semi-supervised word embedding vectors and annotated datasets for different tasks. Our experiments using different algorithms and parameters on our resources show promising results over standard baselines; on average, we achieve a 24.9% relative improvement in F-score on the cross-domain sentiment analysis task when training the same algorithms with our resources, compared to training them on more traditional feature sources, such as n-grams. Importantly, while our resources were built with the primary focus on the cross-domain sentiment analysis task, they also show promising results in related tasks, such as emotion analysis and sarcasm detection. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2018. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2018 holdings: @attributes: islocal: N |
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