Analyzing Election Sentiments in Tweets with Gated Recurrent Units (GRU)
Agu Edward O.,
Bako Jeremy Zevini,
Hambali Moshood Abiola
Abstract:Sentiment analysis, a key task in natural language processing, is important for detecting the emotional tone portrayed in text. In this study, we focus on implementing a Gated Recurrent Unit (GRU) model to analyze attitudes within the 2020 Donald Trump Election tweets dataset. By setting the GRU model with carefully selected parameters, the aim of the study is to unveil the inherent sentiment patterns in the dataset. To develop the sentiment analysis model, the study devised a three phase methodology which t… Show more
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