Zero-shot hashtag segmentation for multilingual sentiment analysis

• URL: http://arxiv.org/abs/2112.03213v1
• Date: Mon, 6 Dec 2021 18:13:46 GMT
• Title: Zero-shot hashtag segmentation for multilingual sentiment analysis
• Authors: Ruan Chaves Rodrigues, Marcelo Akira Inuzuka, Juliana Resplande Sant'Anna Gomes, Acquila Santos Rocha, Iacer Calixto, Hugo Alexandre Dantas do Nascimento
• Abstract summary: Hashtag segmentation, also known as hashtag decomposition, is a common step in preprocessing pipelines for social media datasets. We develop a zero-shot hashtag segmentation framework and demonstrate how it can be used to improve the accuracy of multilingual sentiment analysis pipelines.
• Score: 1.8762753243053634
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Hashtag segmentation, also known as hashtag decomposition, is a common step in preprocessing pipelines for social media datasets. It usually precedes tasks such as sentiment analysis and hate speech detection. For sentiment analysis in medium to low-resourced languages, previous research has demonstrated that a multilingual approach that resorts to machine translation can be competitive or superior to previous approaches to the task. We develop a zero-shot hashtag segmentation framework and demonstrate how it can be used to improve the accuracy of multilingual sentiment analysis pipelines. Our zero-shot framework establishes a new state-of-the-art for hashtag segmentation datasets, surpassing even previous approaches that relied on feature engineering and language models trained on in-domain data.

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