A Kurdish Sorani Twitter dataset for language modelling.

ABSTRACT: Sentiment analysis is an essential task that involves the extraction, identification, characterization, and classification of textual data to understand and categorize the attitudes and opinions expressed by individuals. While other languages have extensive datasets in this field, the number of sentiment analysis datasets in the Kurdish language is extremely limited, highlighting the necessity to build datasets for the language to advance its development. This paper presents a Twitter dataset comprising 24,668 tweets from the initial sample of 30,009 texts. Human annotators labelled the tweets based on subjectivity, sentiment, offensiveness, and target. After the initial annotation, an independent reviewer examined all labelled data to ensure the construction of a robust dataset. The clean

SUBMITTER: Wady SH 

PROVIDER: S-EPMC11491888 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature