Recent Developments in Sentiment Analysis on Social Networks: Techniques, Datasets, and Open Issues

Saxena, Akrati; Reddy, Harita; Saxena, Pratishtha

doi:10.1007/978-981-16-3398-0_13

Cited by 7 publications

(1 citation statement)

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“…In the current literature, there are several works that involve a sentiment analysis on social networks' data. Saxena et al (2022), analyzed the suitability of several techniques, and Chong et al (2014) explored a sentiment analysis on tweets. Further, Kratzwald et al (2018) conducted a relevant work in emotion mining, employing deep learning to distill emotions and formulate decision inputs.…”

Section: Introductionmentioning

confidence: 99%

Analyzing the Emotions That News Agencies Express towards Candidates during Electoral Campaigns: 2018 Brazilian Presidential Election as a Case of Study

Olimpio da Silva,

Losada,

Borondo

2023

Social Sciences

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Since online social networks play an increasingly important role in the final voting decision of each individual, political parties and candidates are changing the way of doing politics and campaigning, increasing their digital presence. In this paper, we propose a methodology to analyze and measure the emotions that news agencies express on social media towards candidates and apply it to the 2018 Brazilian elections. The presented method is based on a sentiment analysis and emotion mining by means of machine learning and Natural Language Processing approaches such as Naïve Bayes classification and Stemming calculation. We found that if doing basic sentiment detection, nearly all posts are neutral. However, when we analyze emotions, following Ekman’s six basic emotions, we do not find neutrality but clear and identifiable emotions. Next, we present and discuss the associative patterns between news agencies and presidential candidates. Finally, since the candidate that captured the highest and most negative attention emerged victorious in the elections, we discuss the potential importance of having a social media presence, regardless of generating positive or negative emotions.

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Section: Introductionmentioning

confidence: 99%