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| Ultima descărcare din IBN: 2022-06-12 13:07 |
 SM ISO690:2012TRANDABĂŢ, Diana, IFTENE, Adrian. Complementing Tweets Sentiment Analysis with Semantic Roles. In: Conference on Mathematical Foundations of Informatics, Ed. 2016, 25-30 iulie 2016, Chișinău. Chișinău, Republica Moldova: "VALINEX" SRL, 2016, pp. 339-348. ISBN 978‐9975‐4237‐4‐8. |
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| Conference on Mathematical Foundations of Informatics 2016 | ||||||
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Conferința "Conference on Mathematical Foundations of Informatics" 2016, Chișinău, Moldova, 25-30 iulie 2016 | ||||||
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| Pag. 339-348 | ||||||
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Slowly but surely, social media replaced the traditional sources of information: people’s need to be constantly updated changed our behavior from buying a newspaper or watching TV, to using a Facebook or Twitter account to visualize, in a customizable manner, the day’s hottest news, with the bonus of being able to also comment on them. This paper presents a method to identify a tweet’s polarity (negative, positive, neutral) using SentiFrameNet, a naïve Bayes classifier and an off-the-self semantic role labeling API. |
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| Cuvinte-cheie natural language processing, sentiment analysis, semantic roles |
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Dublin Core Export
<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc='http://purl.org/dc/elements/1.1/' xmlns:oai_dc='http://www.openarchives.org/OAI/2.0/oai_dc/' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xsi:schemaLocation='http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd'> <dc:creator>Trandabăţ, D.</dc:creator> <dc:creator>Iftene, A.</dc:creator> <dc:date>2016</dc:date> <dc:description xml:lang='en'><p>Slowly but surely, social media replaced the traditional sources of information: people’s need to be constantly updated changed our behavior from buying a newspaper or watching TV, to using a Facebook or Twitter account to visualize, in a customizable manner, the day’s hottest news, with the bonus of being able to also comment on them. This paper presents a method to identify a tweet’s polarity (negative, positive, neutral) using SentiFrameNet, a naïve Bayes classifier and an off-the-self semantic role labeling API.</p></dc:description> <dc:source>Conference on Mathematical Foundations of Informatics () 339-348</dc:source> <dc:subject>natural language processing</dc:subject> <dc:subject>semantic roles</dc:subject> <dc:subject>sentiment analysis</dc:subject> <dc:title>Complementing Tweets Sentiment Analysis with Semantic Roles</dc:title> <dc:type>info:eu-repo/semantics/article</dc:type> </oai_dc:dc>
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