An LSTM model for Twitter Sentiment Analysis
December 04, 2022 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Md Parvez Mollah
arXiv ID
2212.01791
Category
cs.CL: Computation & Language
Cross-listed
cs.SI
Citations
6
Venue
arXiv.org
Last Checked
5 months ago
Abstract
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.
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