Computer Science > Social and Information Networks
[Submitted on 19 Dec 2023 (v1), last revised 17 Jul 2024 (this version, v3)]
Title:Toxic Bias: Perspective API Misreads German as More Toxic
View PDF HTML (experimental)Abstract:Proprietary public APIs play a crucial and growing role as research tools among social scientists. Among such APIs, Google's machine learning-based Perspective API is extensively utilized for assessing the toxicity of social media messages, providing both an important resource for researchers and automatic content moderation. However, this paper exposes an important bias in Perspective API concerning German language text. Through an in-depth examination of several datasets, we uncover intrinsic language biases within the multilingual model of Perspective API. We find that the toxicity assessment of German content produces significantly higher toxicity levels than other languages. This finding is robust across various translations, topics, and data sources, and has significant consequences for both research and moderation strategies that rely on Perspective API. For instance, we show that, on average, four times more tweets and users would be moderated when using the German language compared to their English translation. Our findings point to broader risks associated with the widespread use of proprietary APIs within the computational social sciences.
Submission history
From: Francesco Pierri [view email][v1] Tue, 19 Dec 2023 22:52:51 UTC (1,495 KB)
[v2] Tue, 30 Apr 2024 07:45:00 UTC (1,897 KB)
[v3] Wed, 17 Jul 2024 07:03:57 UTC (1,897 KB)
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