Hindu Muslim Hate Comments Dataset in Bangla (Bangladesh and India)
Description
The religious dataset consisting of Hindu and Muslim hate comments from Bangladesh and India in the Bangla language is a collection of online comments that contain religious hate speech targeting either the Hindu or Muslim communities. These comments were gathered from various sources such as newspapers, social media platforms, and online forums. The purpose of collecting this data is to analyze the prevalence of religious intolerance, identify patterns in hate speech, and contribute to the development of tools for automatically detecting and mitigating such content. Key Features of the Dataset: Source and Collection: Comments were sourced from both Bangladesh and India, reflecting religious sentiments in these neighboring countries where tensions between religious groups have often been a social issue. Sources include Bangla-language social media, news articles, opinion pieces, and comments sections on websites. Content: The dataset contains a mix of both Hindu-targeted hate speech and Muslim-targeted hate speech, with derogatory, offensive, and inflammatory remarks based on religion. Hate comments include stereotypical statements, incitement to violence, communal hatred, and discriminatory language directed at members of the opposing community. Purpose and Use Cases: Hate Speech Detection: This dataset is useful for developing machine learning models that can automatically identify and flag harmful content on social media platforms. Social Science Research: Researchers can study the psychological and sociopolitical factors that drive such hate speech. Policy and Moderation Tools: Governments, social media platforms, and civil society organizations can use insights from this dataset to design anti-hate speech policies and create moderation systems that reduce online hate. Challenges: Contextual Nuances: Understanding the cultural and religious context of Bangla comments is crucial for accurately identifying hate speech. A comment that might seem neutral in one context could be deeply offensive in another. Code-Switching: Some comments might mix Bangla with English or regional languages, complicating the classification and sentiment analysis process. Bias in Data: The dataset might reflect a certain level of social bias depending on the region from which it was collected, which needs to be addressed when training AI models. Conclusion: This dataset offers valuable insights into the dynamics of religious hate speech in Bangladesh and India, two countries with diverse religious populations and a history of interfaith tension. It can help in the development of tools for mitigating online hate speech, while also fostering better understanding and tolerance across religious communities.