Twitter said in April that it was making a new effort to study algorithmic fairness on its platform and whether its algorithms were contributing to “unintended harm.” As part of that work, the company promised to study the political leanings of its content recommendations. Now, the company has released its initial findings. According to Twitter’s research team, the company’s timeline algorithm boosts content from the “political right” in six of the seven countries it studied.
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The research examined two questions: whether algorithmic scheduling boosted political content from elected officials and whether certain political groups received greater boosts. The researchers used tweets from news outlets and elected officials in seven countries (Canada, France, Germany, Japan, Spain, the United Kingdom, and the United States) to conduct the analysis, which was the first of its kind for Twitter.
Crucially, as Chowdhury points out in Protocol, it’s not yet clear why this is happening. In the paper, the researchers suggest that the difference in amplification could be a result of political parties pursuing “different Twitter strategies.” But the team said more research will be needed to fully understand the cause.
While the findings are likely to raise some concern, Rumman Chowdhury also notes that “algorithmic amplification is not problematic by default.” The researchers point out that their findings “do not support the hypothesis that algorithmic personalization amplifies extreme ideologies more than mainstream political voices.”.
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But at the very least, the research seems to debunk the idea that Twitter is biased against conservatives. The study also offers an interesting look at how a tech platform can study the unintended consequences of its algorithms. Facebook, which has come under pressure to release more of its own research, defended its algorithms even when a whistleblower suggested the company should return to a chronological timeline.
Twitter's investigation is part of a broader effort by Twitter to uncover any bias or other issues in its algorithms.
Information source: engadget.com
