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An Emotional Word Analyzer for Portuguese

Authors: Maria Inês Maia and José Paulo Leal

Published in: OASIcs, Volume 56, 6th Symposium on Languages, Applications and Technologies (SLATE 2017)


Abstract
The analysis of sentiments, emotions and opinions in texts is increasingly important in the current digital world. The existing lexicons with emotional annotations for the Portuguese language are oriented to polarities, classifying words as positive, negative or neutral. To identify the emotional load intended by the author it is necessary also to categorize the emotions expressed by individual words. EmoSpell is an extension of a morphological analyzer with semantic annotations of the emotional value of words. It uses Jspell as the morphological analyzer and a new dictionary with emotional annotations. This dictionary incorporates the lexical base EMOTAIX.PT, which classifies words based on three different levels of emotions - global, specific and intermediate. This paper describes the generation of the EmoSpell dictionary using three sources, the Jspell Portuguese dictionary and the lexical bases EMOTAIX.PT and SentiLex-PT. Also, this paper details the web application and web service that exploit this dictionary. It presents also a validation of the proposed approach using a corpus of student texts with different emotional loads. The validation compares the analyses provided by EmoSpell with the mentioned emotional lexical bases on the ability to recognize emotional words and extract the dominant emotion from a text.

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Maria Inês Maia and José Paulo Leal. An Emotional Word Analyzer for Portuguese. In 6th Symposium on Languages, Applications and Technologies (SLATE 2017). Open Access Series in Informatics (OASIcs), Volume 56, pp. 17:1-17:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


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@InProceedings{maia_et_al:OASIcs.SLATE.2017.17,
  author =	{Maia, Maria In\^{e}s and Leal, Jos\'{e} Paulo},
  title =	{{An Emotional Word Analyzer for Portuguese}},
  booktitle =	{6th Symposium on Languages, Applications and Technologies (SLATE 2017)},
  pages =	{17:1--17:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-056-9},
  ISSN =	{2190-6807},
  year =	{2017},
  volume =	{56},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Sim\~{o}es, Alberto and Leal, Jos\'{e} Paulo and Varanda, Maria Jo\~{a}o},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2017.17},
  URN =		{urn:nbn:de:0030-drops-79585},
  doi =		{10.4230/OASIcs.SLATE.2017.17},
  annote =	{Keywords: Sentiment Analysis, Opinion Mining, Emotion API}
}
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