Echoes of Equity: A Balanced Sentiment Dataset of Bangladesh’s Anti-Discrimination Student Movement
Description
Movements for social justice are more than simply events; they are discussions, feelings, and arguments that have a long-lasting impact. The Anti-Discrimination Student Movement in Bangladesh sparked one such discussion, illustrating the complexities of popular feeling towards fairness and rights. For decoding these narratives, we provide Echoes of Equity, a dataset of 3,057 labelled items that capture the whole range of sentiment—999 positive, 1,043 negative, and 1,015 neutral sentences. This dataset, derived from real-world speech such as newspapers, social media, and other public forums, provides a window into the emotional and rhetorical fabric of a historic movement while also serving as a unique resource for sentiment analysis, discourse analysis, and computational sociology. Key statistical studies, such as class-based summary statistics, histograms, word clouds, and unigram, bigram, and trigram patterns, etc. are useful in understanding the dataset's structure and linguistic variety. Echoes of Equity serves as a foundation for constructing sophisticated NLP tools capable of comprehending the nuances of social movements, with strict attention to data integrity through anonymisation, rigorous data gathering, and preprocessing. This dataset is useful for constructing context-sensitive natural language processing (NLP) models and gaining a better understanding of public opinion in key social movements since it provides fair representation across sentiment categories. Beyond computational applications, this resource encourages cross-disciplinary research, providing insights into the dynamics of public opinion, activism, and social change. This dataset captures the intricacies of public opinion around this movement, laying the groundwork for sentiment analysis and computational research. It contributes significantly to understanding public opinion and sets the path for further investigation of sociopolitical movements using computational approaches. This dataset, which is open to the public, seeks to be both a mirror for previous battles and a tool for crafting fair futures, and it promotes collaboration and creativity, adding to the worldwide repertory of computational tools used to analyse social justice movements. We intend to foster multidisciplinary study on the movement's societal impact, develop sentiment analysis, and contribute to the documentation of Bangladesh's sociopolitical history.