Twitter admits bias in algorithm for rightwing politicians and news outlets
Twitter has admitted it amplifies more tweets from rightwing politicians and news outlets than content from leftwing sources. The company examined tweets from elected officials in seven countries – the UK, US, Canada, France, Germany, Spain and Japan. It also studied whether political content from news organisations was amplified on Twitter, focusing primarily on US news sources such as Fox News, the New York Times and BuzzFeed. The study compared Twitter’s “Home” timeline – the default way its 200 million users are served tweets, in which an algorithm tailors what users see – with the traditional chronological timeline where the most recent tweets are ranked first. The research found that in six out of seven countries, apart from Germany, tweets from rightwing politicians received more amplification from the algorithm than those from the left; right-leaning news organisations were more amplified than those on the left; and generally politicians’ tweets were more amplified by an algorithmic timeline than by the chronological timeline. Twitter found a “statistically significant difference favouring the political right wing” in all the countries except Germany. Under the research, a value of 0% meant tweets reached the same number of users on the algorithm-tailored timeline as on its chronological counterpart, whereas a value of 100% meant tweets achieved double the reach. On this basis, the most powerful discrepancy between right and left was in Canada (Liberals 43%; Conservatives 167%), followed by the UK (Labour 112%; Conservatives 176%). Even excluding top government officials, the results were similar. Twitter said it wasn’t clear why its Home timeline produced these results and indicated that it may now need to change its algorithm.
Twitter admits bias in algorithm for rightwing politicians and news outlets Algorithmic Amplification of Politics on Twitter (read the research) Examining algorithmic amplification of political content on Twitter (Twitter blog post)