2015
DOI: 10.3233/ia-150076
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State of the Art Language Technologies for Italian: The EVALITA 2014 Perspective

Abstract: Abstract. Shared task evaluation campaigns represent a well established form of competitive evaluation, an important opportunity to propose and tackle new challenges for a specific research area and a way to foster the development of benchmarks, tools and resources. The advantages of this approach are evident in any experimental field, including the area of Natural Language Processing. An outlook on state-of-the-art language technologies for Italian can be obtained by reflecting on the results of the recently … Show more

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Cited by 11 publications
(10 citation statements)
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“…In order to overcome this limitation, we plan to develop a preliminary sentiment analysis system by automatically translating the lexical resources available for English to French and by developing a reduced corpus of manually annotated tweets to train the system, by adapting the methodologies applied in [26] in the contest of the Sentiment POLarity Classification shared task proposed at the Evalita evaluation campaign on of natural language processing and speech tools for Italian [27], [28]. For what concerns the sentiment analysis issue, we should investigate also the use of a linguistic knowledge derived by a more structured and wider notion of context which includes syntactic chunks or spans over a large word space, or the exploitation of domain-independent expressive signals such as emoticons and emojis.…”
Section: Discussionmentioning
confidence: 99%
“…In order to overcome this limitation, we plan to develop a preliminary sentiment analysis system by automatically translating the lexical resources available for English to French and by developing a reduced corpus of manually annotated tweets to train the system, by adapting the methodologies applied in [26] in the contest of the Sentiment POLarity Classification shared task proposed at the Evalita evaluation campaign on of natural language processing and speech tools for Italian [27], [28]. For what concerns the sentiment analysis issue, we should investigate also the use of a linguistic knowledge derived by a more structured and wider notion of context which includes syntactic chunks or spans over a large word space, or the exploitation of domain-independent expressive signals such as emoticons and emojis.…”
Section: Discussionmentioning
confidence: 99%
“…Not surprisingly, most applications of this kind are based on English. Italian is used much less frequently (a few examples are Bosco, Patti, and Bolioli 2013;Bosco et al 2014;Bosco, Patti, and Bolioli 2015;Barbieri et al 2016), although there has been some evaluation of Italian NLP tools and resources (Attardi et al 2015;Basile et al 2016).…”
Section: Related Workmentioning
confidence: 99%
“…The majority of the research in irony detection has been addressed in English, although there is some research in other languages, such as: Dutch [Kunneman et al 2015], Italian [Bosco et al 2013], Czech [Ptáček et al 2014], French [Karoui et al 2015], Portuguese [Carvalho et al 2009] and Chinese [Tang and Chen 2014]. A shared task for English on sentiment analysis of figurative language in Twitter has been organized at SemEval-2015 for the first time [Ghosh et al 2015], and a pilot shared task for Italian on irony detection has been proposed in Sentipolc-2014 within the periodic evaluation campaign EVALITA [Basile et al 2014;Attardi et al 2015]. This confirms the growing interest for this task in the research community, especially for understanding the impact of the ironic devices on sentiment analysis.…”
Section: Related Workmentioning
confidence: 99%