ArSen-20: A New Benchmark for Arabic Sentiment Detection
Keywords: Sentiment Detection, Benchmark, Arabic
TL;DR: ArSen-20 is a dataset of 20,000 Arabic tweets about COVID-19 from 2020 to 2023, including user metadata, to advance sentiment analysis in Arabic NLP.
Abstract: Sentiment detection remains a pivotal task in natural language processing, yet its development in Arabic lags due to a scarcity of training materials compared to English. Addressing this gap, we present ArSen-20, a benchmark dataset tailored to propel Arabic sentiment detection forward. ArSen-20 comprises 20,000 professionally labeled tweets sourced from Twitter, focusing on the theme of COVID-19 and spanning the period from 2020 to 2023. Beyond tweet content, the dataset incorporates metadata associated with the user, enriching the contextual understanding. ArSen-20 offers a comprehensive resource to foster advancements in Arabic sentiment analysis and facilitate research in this critical domain.
Submission Number: 20
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