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9th World Conference on Information Systems and Technologies

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Computerised Sentiment Analysis On Socialnetworks. Two Case Studies: Fifa World Cup 2018and Cristiano Ronaldo Joining Juventus

Sentiment analysis on social networks plays a prominent role inmany applications. The key techniques here are how to identify opinions, toclassify sentiment polarity, and to infer emotions. In this study, we proposeda sentence-level sentiment analysis based on a microblogging platform likeTwitter. Comprehensive evaluation results on real-world scenarios such as theFIFA World Cup 2018, and the Cristiano Ronaldo’s transfer to Juventus inthe summer of 2018 demonstrate a correlation between the polarity (nega-tive or positive) and fan’s sentiments. In addition, the evaluation of severalmachine learning techniques; applied to identify the polarity and related emo-tions, revealed that the SVM outperforms other models such as Naive Bayes,ANN, kNN, and Logistic Regression. Additional studies should be addressedto evaluate the proposed system on different sport events, and scenarios.

Nuno Pombo
Universidade da Beira Interior
Portugal

Miguel Rodrigues
Computerised Sentiment Analysis on SocialNetworks. Two case studies: FIFA World Cup 2018and Cristiano Ronaldo joining Juventus
Portugal

Zdenka Babic
University of Banja Luka, Faculty of Electrical Engineering
Bosnia and Herzegovina

Magdalena Punceva
University of Applied Sciences and Arts Western Switzerland
Switzerland

Nuno Garcia
Universidade da Beira Interior
Portugal

 


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