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Aspect based sentiment analysis datasets for Bangla text.

Mahmudul Hasan1,2, Md Rashedul Ghani1, K M Azharul Hasan1

  • 1Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh.

Data in Brief
|December 6, 2024
PubMed
Summary
This summary is machine-generated.

Researchers developed BANGLA_ABSA, a new dataset for Aspect Based Sentiment Analysis (ABSA) in Bangla social media text. This resource addresses the challenge of limited data for analyzing Bangla sentiment by aspect.

Keywords:
Aspect based sentiment analysisBangla sentiment analysisNatural language processingOpinion miningSentiment analysis

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Area of Science:

  • Natural Language Processing
  • Computational Linguistics
  • Social Media Analysis

Background:

  • Sentiment analysis of Bangla social media text is crucial but hindered by a lack of annotated resources.
  • Aspect Based Sentiment Analysis (ABSA) requires detailed data for identifying sentiment towards specific aspects within text.

Purpose of the Study:

  • To address the scarcity of resources for Bangla Aspect Based Sentiment Analysis (ABSA).
  • To introduce a high-quality, manually annotated dataset for ABSA in the Bangla language.

Main Methods:

  • Development of a new annotated dataset named BANGLA_ABSA.
  • Manual annotation of comments across four domains: Restaurant, Movie, Mobile phone, and Car.
  • Dataset organized into tuples of {Id, Comment, Aspect Category, Sentiment Polarity}.

Main Results:

  • Creation of four domain-specific datasets: Restaurant_ABSA (801 comments), Movie_ABSA (800 comments), Mobile_phone_ABSA (975 comments), and Car_ABSA (1149 comments).
  • All annotated comments are complex or compound sentences, providing rich linguistic data.
  • The dataset is structured for efficient use in machine learning and deep learning research.

Conclusions:

  • The BANGLA_ABSA dataset is a significant contribution to Bangla Natural Language Processing research.
  • This resource will facilitate advancements in sentiment analysis and machine learning for Bangla text.
  • Enables more sophisticated aspect-based sentiment analysis for Bangla social media content.