Integrating hashtags in sentiment analysis on Twitter posts in Spanish language using BETO
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2022-07-08
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en
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Abstract
Amongst the latest developments in Natural language processing are pretrained
transformers. One field in which they are used is sentiment analysis,
which seeks to identify the intent or emotion expressed in a text. Hashtags
in social media texts, such as tweets, are often removed as part of the
pre-processing. As hashtags can contain important information or necessary
context to understand the sentiment of a tweet, removing them can
reduce the classification performance. In this study we performed sentiment
analysis with a pre-trained BETO model on Spanish tweets that have
the Chilean dictator Pinochet as topic. We show that including hashtags
into sentiment analysis can increase f1-score. This indicates that changes
in pre-processing procedures can increase efficiency of Natural Language
Processing approaches.
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Faculteit der Sociale Wetenschappen