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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 7 of 7 1 A sentiment analysis approach to increase authorship identification Martins, Ricardo; Almeida, J. J.; Henriques, Pedro Rangel; Novais, Paulo. - : Wiley, 2021 Abstract: Writing style is considered the manner in which an author expresses his thoughts, influenced by language characteristics, period, school, or nation. Often, this writing style can identify the author. One of the most famous examples comes from 1914 in Portuguese literature. With Fernando Pessoa and his heteronyms Alberto Caeiro, alvaro de Campos, and Ricardo Reis, who had completely different writing styles, led people to believe that they were different individuals. Currently, the discussion of authorship identification is more relevant because of the considerable amount of widespread fake news in social media, in which it is hard to identify who authored a text and even a simple quote can impact the public image of an author, especially if these texts or quotes are from politicians. This paper presents a process to analyse the emotion contained in social media messages such as Facebook to identify the author's emotional profile and use it to improve the ability to predict the author of the message. Using preprocessing techniques, lexicon-based approaches, and machine learning, we achieved an authorship identification improvement of approximately 5% in the whole dataset and more than 50% in specific authors when considering the emotional profile on the writing style, thus increasing the ability to identify the author of a text by considering only the author's emotional profile, previously detected from prior texts. ; FCT has supported this work – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019. Keyword: Ciências Naturais::Ciências da Computação e da Informação; Eletrónica e Informática; Engenharia e Tecnologia::Engenharia Eletrotécnica; machine learning; natural language processing; Science & Technology; sentiment analysis URL: https://doi.org/10.1111/exsy.12469 http://hdl.handle.net/1822/68848 BASE Hide details 2 Predicting Performance Problems Through Emotional Analysis (Short Paper) Martins, Ricardo; Henriques, Pedro Rangel; Novais, Paulo. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2018. : OASIcs - OpenAccess Series in Informatics. 7th Symposium on Languages, Applications and Technologies (SLATE 2018), 2018 BASE Show details 3 Predicting Performance Problems Through Emotional Analysis (Short Paper) ... Martins, Ricardo; Almeida, José João; Henriques, Pedro Rangel. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Wadern/Saarbruecken, Germany, 2018 BASE Show details 4 Predicting performance problems through emotional analysis Martins, Ricardo; Almeida, José João; Henriques, Pedro Rangel. - : Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH, 2018 BASE Show details 5 Increasing authorship identification through emotional analysis Martins, Ricardo; Almeida, J. J.; Henriques, Pedro Rangel. - : Springer Verlag, 2018 BASE Show details 6 Hate speech classification in social media using emotional analysis Martins, Ricardo; Gomes, Marco Filipe Vieira; Almeida, J. J.. - : IEEE, 2018 BASE Show details 7 Creating a social media-based personal emotional lexicon Martins, Ricardo; Almeida, J. J.; Novais, Paulo. - : Association for Computing Machinery, 2018 BASE Show details

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