While colonization has sociohistorically impacted people's identities across various dimensions, those colonial values and biases continue to be perpetuated by sociotechnical systems. One category of sociotechnical systems--sentiment analysis tools--can also perpetuate colonial values and bias, yet less attention has been paid to how such tools may be complicit in perpetuating coloniality, although they are often used to guide various practices (e.g., content moderation). In this paper, we explore potential bias in sentiment analysis tools in the context of Bengali communities that have experienced and continue to experience the impacts of colonialism. Drawing on identity categories most impacted by colonialism amongst local Bengali communities, we focused our analytic attention on gender, religion, and nationality. We conducted an algorithmic audit of all sentiment analysis tools for Bengali, available on the Python package index (PyPI) and GitHub. Despite similar semantic content and structure, our analyses showed that in addition to inconsistencies in output from different tools, Bengali sentiment analysis tools exhibit bias between different identity categories and respond differently to different ways of identity expression. Connecting our findings with colonially shaped sociocultural structures of Bengali communities, we discuss the implications of downstream bias of sentiment analysis tools.

在这篇论文中，我们探讨了社会技术系统（情感分析工具）中潜在的偏见，并对具有殖民主义影响的孟加拉社群中的性别、宗教和国籍等身份类别进行了分析。通过对所有孟加拉情感分析工具进行算法审计，我们发现这些工具不仅在输出上存在不一致性，而且在不同身份表达方式下存在偏见。我们将研究结果与孟加拉社群的殖民主义社会文化结构联系起来，并探讨了情感分析工具下游偏见的影响。

自然语言处理的“殖民冲动”：孟加拉情感分析工具及其基于身份的偏见审计