Datasets for Aspect-Based Sentiment Analysis in Bangla and Its Baseline Evaluation

Md. Atikur Rahman and Emon Kumar Dey
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Md. Atikur Rahman: Institute of Information Technology, University of Dhaka, Dhaka 1000, Bangladesh
Emon Kumar Dey: Institute of Information Technology, University of Dhaka, Dhaka 1000, Bangladesh

Data, 2018, vol. 3, issue 2, 1-10

Abstract: With the extensive growth of user interactions through prominent advances of the Web, sentiment analysis has obtained more focus from an academic and a commercial point of view. Recently, sentiment analysis in the Bangla language is progressively being considered as an important task, for which previous approaches have attempted to detect the overall polarity of a Bangla document. To the best of our knowledge, there is no research on the aspect-based sentiment analysis (ABSA) of Bangla text. This can be described as being due to the lack of available datasets for ABSA. In this paper, we provide two publicly available datasets to perform the ABSA task in Bangla. One of the datasets consists of human-annotated user comments on cricket, and the other dataset consists of customer reviews of restaurants. We also describe a baseline approach for the subtask of aspect category extraction to evaluate our datasets.

Keywords: ABSA dataset; Bangla ABSA; aspect extraction from Bangla (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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