Bangla Text Dataset and Exploratory Analysis for Online Harassment Detection
This dataset addresses the scarcity of categorized Bangla text data for online harassment detection, which is crucial for researchers and developers working on safety in online Bangla-speaking communities.
This paper introduces a new dataset of 44,001 Bangla comments collected from Facebook posts of public figures, labeled for various categories of online harassment. The dataset aims to facilitate the development of machine learning models for detecting and classifying bullying and inappropriate content in Bangla.
Being the seventh most spoken language in the world, the use of the Bangla language online has increased in recent times. Hence, it has become very important to analyze Bangla text data to maintain a safe and harassment-free online place. The data that has been made accessible in this article has been gathered and marked from the comments of people in public posts by celebrities, government officials, athletes on Facebook. The total amount of collected comments is 44001. The dataset is compiled with the aim of developing the ability of machines to differentiate whether a comment is a bully expression or not with the help of Natural Language Processing and to what extent it is improper if it is an inappropriate comment. The comments are labeled with different categories of harassment. Exploratory analysis from different perspectives is also included in this paper to have a detailed overview. Due to the scarcity of data collection of categorized Bengali language comments, this dataset can have a significant role for research in detecting bully words, identifying inappropriate comments, detecting different categories of Bengali bullies, etc. The dataset is publicly available at https://data.mendeley.com/datasets/9xjx8twk8p.