What Drives Sentiments on Social Media? An Exploratory Study on the 2021 Canadian Federal Election

Date
2023-01-03
Authors
Noor, Hiba Mohammad
Turetken, Ozgur
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2170
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Social media is used for online political discourse. Voter opinions have different sentiments associated with them. Understanding the factors behind these sentiments can help policymakers to take actions that align with voter needs and priorities. This research focuses on identifying the drivers (keywords) of sentiments while also investigating the relationship between these keywords and how fast the related message (the tweet) spreads. Sentiment Analysis (SA) of 779,169 tweets related to the 2021 Canadian Federal election was followed by text clustering to identify sentiment-driving topics. The results suggest some keywords common in opposite sentiment types (positive and negative), which shows polarization in Twitter while some keywords unique to a sentiment type suggest concepts to invest in or mitigate. Chi-Square tests suggest a significant relationship between keywords and the number of retweets for extremely negative tweets.
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Data Analytics, Data Mining, and Machine Learning for Social Media, canadian politics, political discourse, sentiment analysis, social media, text analytics
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10
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Proceedings of the 56th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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