Conducting Sentiment Analysis on Twitter Tweets to Predict the Outcomes of the Upcoming Karnataka State Elections

Prajwal Madhusudhana Reddy
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Abstract

- This research paper aims to predict how Twitter tweets from a specific politician correlate to their winning a seat in a state election. To understand this effect, sentiment analysis has been conducted on tweets by politicians in Karnataka to help predict who will win in the upcoming 2023 Karnataka Legislative Assembly election. Though previous research has already been done in this area, most studies have only focussed on the sentiment analysis of tweets. This paper goes further as it also looks at other factors, including the number of retweets and comments a tweet garners, which measures the tweet's engagement. A model has been created that weighs each factor to help predict who will win an election for a particular constituency. Through this model, a 72.7% accuracy has been achieved. However, the Twitter API severely limited the quantity and quality of data collected. These results can be expanded to help predict elections for other states. They could potentially help understand the effect of positive and negative sentiment on the winnability of a political candidate.
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对推特推文进行情感分析以预测即将到来的卡纳塔克邦选举的结果
-这篇研究论文旨在预测特定政客的推文与他们在州选举中赢得席位的关系。为了理解这种影响,对卡纳塔克邦政客的推文进行了情绪分析,以帮助预测谁将在即将到来的2023年卡纳塔克邦立法议会选举中获胜。虽然之前的研究已经在这一领域进行了,但大多数研究只关注推文的情感分析。这篇论文走得更远,因为它还考虑了其他因素,包括一条推文获得的转发和评论数量,这衡量了推文的参与度。已经建立了一个模型来衡量每个因素,以帮助预测谁将赢得特定选区的选举。通过该模型,准确率达到了72.7%。然而,Twitter API严重限制了所收集数据的数量和质量。这些结果可以扩展到帮助预测其他州的选举。它们可能有助于理解积极和消极情绪对政治候选人获胜能力的影响。
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