Twitter has confessed that it promotes right-wing politicians and news organizations’ posts more than left-wing sources.
With the exception of Germany, a study discovered that tweets from right-wing politicians were amplified by the algorithm more than those from the left; right-leaning news organizations were amplified more than those on the left; and, in general, politicians’ tweets were amplified by an algorithmic timeline rather than a chronological timeline.
“According to a 27-page research document, Twitter found a “statistically significant difference favouring the political right wing” in all the countries except Germany… 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%).”From The Guardian article, “Twitter admits bias in algorithm for rightwing politicians and news outlets”
Twitter stated that it was unclear why its Home timeline produced these results and that the algorithm may need to be changed. If specific tweets gained preferential treatment as a consequence of how people interacted with the algorithm shaping their timeline, it is concerning.
If there is preferential treatment based on how the algorithm is built versus how people interact with it, algorithmic amplification becomes a concern. Further root cause analysis is needed to evaluate what, if any, improvements are necessary to mitigate the negative effects of our Home timeline algorithm.
Twitter has had a history of problematic biases in algorithms. Twitter revealed in May that its automatic cropping algorithm has regularly cropped out Black faces in favor of light-skinned ones and favored males over women, in response to user complaints. It has sought to resolve such concerns since then, according to the business. It is harder to try to distinguish what exactly is causing the bias, whether it is from user interaction or internal wiring since it is a program.
Twitter stated that it would make its research available to third parties, but that it would not make the “raw data” public due to privacy concerns. “We are making aggregated datasets accessible for third-party researchers who desire to duplicate our primary findings and confirm our methods upon request,” according to the article.
Twitter also stated that it was planning to regularly make internal data public to external sources. The business’s machine-learning ethics, transparency, and accountability team is finalizing strategies to protect user privacy, according to the corporation.