A recent study by the Distributed AI Research Institute, examining content moderation during the 2020–2022 war in Ethiopia’s Tigray region has found that social media platforms “failed to adequately moderate genocidal content,” allowing hate speech, violent incitement, and denial of atrocities to circulate widely online. To understand the expertise required to moderate wartime content, the researchers conducted a four-month annotation study of 340 X (formerly Twitter) posts drawn from a dataset of 5.5 million. Seven experts fluent in Amharic, Tigrinya, Arabic, and English took part in the labeling process. “We found that dialectical knowledge, including slang terms, was crucial in identifying harmful posts,” the authors wrote.

However, even among these experts, initial disagreement was high. The study reported that “our experts started out disagreeing 71% of the time,” a rate that decreased to 40% following five deliberation meetings. “Each post they disagreed on was annotated by the reason of disagreement, and final labels decided on after discussion,” the paper noted. One example reviewed by the annotators involved a post containing the hashtag “#FakeAxumMassacre.” The post was classified under the category “Violent Event Denial.” The researchers noted that although “the event was recounted by survivors and investigated and corroborated by the likes of Amnesty International, Human Rights Watch and Associated Press,” the post “claims that the massacre is ‘fake.’” ; In another instance, a post translated from Amharic as “Clean the cockroaches” was not flagged by all annotators. The study stated that “in order to identify this post as genocidal content, one would need to know that the Ethiopian government and its allies regularly described Tigrayans as cockroaches.” One annotator who was in Tigray during the blackout did not recognize the context, while another—based in the diaspora—who had been “independently studying and archiving harmful social media posts during the genocide” quickly identified this post as genocidal content.

The researchers also interviewed 15 commercial content moderators who worked in African content markets, including Ethiopia. “Content moderators are prevented from raising such disagreements by organizational hierarchies, exploitative working conditions, and inflexible platform policies,” the report concluded. Moderators cited vague rules, lack of training, and the inability to influence platform decisions. “We turn [moderators] into robots, we force them to understand policy (…) So it’s not about what you know, what you think you know, it’s what policy says,” one quality analyst is quoted as saying. Another participant stated, “They didn’t even tell me what the job really entails. (…) Unfortunately, when I came here [and worked as a content moderator], that’s [when] I then realized that (…) it’s really not what I thought it is.” The study found that commercial moderators often lacked the conditions to make informed decisions while also facing surveillance and punitive evaluation metrics. Annotators in the research setting, by contrast, were not time-constrained and had the opportunity to deliberate on disagreements, which the authors described as a crucial factor for consistent labeling.

Business and Human Rights Resource Centre invited X (formerly Twitter) to respond. X (formerly Twitter) did not respond