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An LSTM model for Twitter Sentiment Analysis

arXiv 2212.01791 ↗First posted 4 Dec 2022cs.CL cs.SIcited by 1

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Abstract (arXiv)

Sentiment analysis on social media such as Twitter provides organizations and individuals an effective way to monitor public emotions towards them and their competitors. As a result, sentiment analysis has become an important and challenging task. In this work, we have collected seven publicly available and manually annotated twitter sentiment datasets. We create a new training and testing dataset from the collected datasets. We develop an LSTM model to classify sentiment of a tweet and evaluate the model with the new dataset.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 1 of its 17 references that are in the map. First posted on arXiv 4 Dec 2022.

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1 of 17 references.

References · 1

  1. 2019SemEval-2014 Task 9: Sentiment Analysis in Twittercited by 20

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