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A sentiment analysis approach to increase authorship identification
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Structural onomatology for username generation: A partial account
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Cidades Inteligentes: Proposta de modelagem regulatória para a governação participativa, no contexto luso-brasileiro
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Predicting Performance Problems Through Emotional Analysis (Short Paper)
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Predicting Performance Problems Through Emotional Analysis (Short Paper) ...
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Increasing authorship identification through emotional analysis
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Hate speech classification in social media using emotional analysis
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Creating a social media-based personal emotional lexicon
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Abstract:
One of the major problems when using lexicon in sentiment analysis is that they do not cover all possible words in a text and frequently they miss the more expressive to describe the emotions of the text's author efficiently. This problem occurs because people in non-official, on formal channels, communicate using slangs, neologisms, new patterns based on abbreviations (as "aka", "brb" and "asap") and the different meanings, making challenging to analyse texts using a finite subset of a language. This is a problem because some unknown words can completely change the meaning of a sentence, producing misunderstandings. In this paper we present an approach to expand an emotional lexicon for a specific author, producing a customised lexicon which represents how the author "feels" the words. In our experiments, we got an increase of 35.34% and 107.02% in the dictionary size when compared to the original lexicon using two different authors, and identifying different emotions from the same text according to each author's lexicon, i.e. interpreting the text according to the author's "point of view". ; This work has been supported by COMPETE: POCI-01-0145-FEDER-0070 43 and FCT - Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/2013.
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Keyword:
Ciências Naturais::Ciências da Computação e da Informação; Eletrónica e Informática; Engenharia e Tecnologia::Engenharia Eletrotécnica; Machine Learning; Natural Processing Language; Science & Technology; Sentiment Analysis
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URL: http://hdl.handle.net/1822/68818 https://doi.org/10.1145/3243082.3264668
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An application to enrich the study of auditory emotion recognition
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Selection of a visible-light vs. Thermal infrared sensor in dynamic environments based on confidence measures
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Online dispute resolution: an artificial intelligence perspective
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The relationship between stress and conflict handling style in an ODR environment
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Using case-based reasoning to support alternative dispute resolution
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