Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American English
University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校）
英文摘要：
We highlight an important frontier in algorithmic fairness: disparity in the quality of natural language processing algorithms when applied to language from authors of different social groups. For example, current systems sometimes analyze the language of females and minorities more poorly than they do of whites and males. We conduct an empirical analysis of racial disparity in language identification for tweets written in African-American English, and discuss implications of disparity in NLP.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
