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Sentiment analysis of news titles: The role of entities and a new affective lexicon
Abstract The growth of content on the web has been The growth of content on the web has been followed by increasing interest in opinion mining. This field of research relies on accurate recognition of emotion from textual data. There's been much research in sentiment analysis lately, but it always focuses on the same elements. Sentiment analysis traditionally depends on linguistic corpora, or common sense knowledge bases, to provide extra dimensions of information to the text being analyzed. Previous research hasn't yet explored a fully automatic method to evaluate how events associated to certain entities may impact each individual's sentiment perception. This project presents a method to assign valence ratings to entities, using information from their Wikipedia page, and considering user preferences gathered from the user's Facebook profile. Furthermore, a new affective lexicon is compiled entirely from existing corpora, without any intervention from the coders. without any intervention from the coders.
Abstractsub The growth of content on the web has been The growth of content on the web has been followed by increasing interest in opinion mining. This field of research relies on accurate recognition of emotion from textual data. There's been much research in sentiment analysis lately, but it always focuses on the same elements. Sentiment analysis traditionally depends on linguistic corpora, or common sense knowledge bases, to provide extra dimensions of information to the text being analyzed. Previous research hasn't yet explored a fully automatic method to evaluate how events associated to certain entities may impact each individual's sentiment perception. This project presents a method to assign valence ratings to entities, using information from their Wikipedia page, and considering user preferences gathered from the user's Facebook profile. Furthermore, a new affective lexicon is compiled entirely from existing corpora, without any intervention from the coders. without any intervention from the coders.
Bibtextype inproceedings  +
Doi 10.1007/978-3-642-24769-9_1  +
Has author Loureiro D. + , Marreiros G. + , Neves J. +
Has extra keyword Automatic method + , Commonsense knowledge + , Extra dimensions + , Facebook + , Opinion mining + , Recognition of emotion + , Sentiment analysis + , Textual data + , Wikipedia + , Artificial intelligence + , Research + , User interfaces + , Data mining +
Isbn 9783642247682  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 1–14  +
Published in Lecture Notes in Computer Science +
Title Sentiment analysis of news titles: The role of entities and a new affective lexicon +
Type conference paper  +
Volume 7026 LNAI  +
Year 2011 +
Creation dateThis property is a special property in this wiki. 8 November 2014 05:39:44  +
Categories Publications without keywords parameter  + , Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 8 November 2014 05:39:44  +
DateThis property is a special property in this wiki. 2011  +
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Sentiment analysis of news titles: The role of entities and a new affective lexicon + Title
 

 

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