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.
翻译:作为世界上第七种最通用的语言,孟加拉语在网上的使用近年来有所增加,因此,分析孟加拉语文本数据以维持一个安全和无骚扰的在线场所变得非常重要。本篇文章中提供的数据已经收集起来,并根据名人、政府官员、脸书上的运动员在公共职位上的评论作了标记。收集到的评论总数为44001份。数据集的汇编旨在发展机器的能力,以区分评论是否是一种欺凌的表达方式,在自然语言处理的帮助下,以及如果它是不适当的评论,这种评论在多大程度上是不适当的。评论被贴上不同类别的骚扰标签。从不同角度进行的探讨性分析也列入本文,以便有详细的概览。由于收集的分类孟加拉语评论很少,这一数据集在查找欺凌言词、查明不适当的评论、发现不同类别的孟加拉语霸凌等等方面可以发挥重大作用。数据集在https://data.mendeley.com/datastststses/9/xx8twk8p上公布。