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While colonization has sociohistorically impacted people's identities acrossvarious dimensions, those colonial values and biases continue to be perpetuatedby sociotechnical systems. One category of sociotechnical systems--sentimentanalysis tools--can also perpetuate colonial values and bias, yet lessattention has been paid to how such tools may be complicit in perpetuatingcoloniality, although they are often used to guide various practices (e.g.,content moderation). In this paper, we explore potential bias in sentimentanalysis tools in the context of Bengali communities that have experienced andcontinue to experience the impacts of colonialism. Drawing on identitycategories most impacted by colonialism amongst local Bengali communities, wefocused our analytic attention on gender, religion, and nationality. Weconducted an algorithmic audit of all sentiment analysis tools for Bengali,available on the Python package index (PyPI) and GitHub. Despite similarsemantic content and structure, our analyses showed that in addition toinconsistencies in output from different tools, Bengali sentiment analysistools exhibit bias between different identity categories and responddifferently to different ways of identity expression. Connecting our findingswith colonially shaped sociocultural structures of Bengali communities, wediscuss the implications of downstream bias of sentiment analysis tools.

The "Colonial Impulse" of Natural Language Processing: An Audit of Bengali Sentiment Analysis Tools and Their Identity-based Biases