Twitter’s algorithm favors more right-wing news outlets than others, according to internal research posted on its website Thursday — but the social network isn’t exactly sure.
Since April, the company has investigated whether, and how, its algorithm that recommends content to users, amplifies political content.
In six out of seven countries – all except Germany – tweets posted by accounts from the political right appear to have received greater exposure by the algorithm than by the political left when studied as a group.
The first part of the study examined millions of tweets posted by elected officials, such as lawmakers, in seven countries – Canada, France, Germany, Japan, Spain, the UK and the US – between April 1 and August 15, 2020.
The company used this data to test whether these tweets were more amplified on an algorithmically-ordered “timeline” of tweets than on a reverse-chronological feed, and whether there were different types of results within a political party. .
Twitter also studied whether its recommendation algorithms increase political content from news outlets.
To do this, the company also analyzed hundreds of millions of tweets containing links to news shared by people on Twitter between April and August last year.
The researchers found that right-leaning news outlets see more algorithmic amplification on Twitter than left-leaning news outlets. Preliminary results only show a bias in amplification, not what is causing it.
Rumman Choudhury, head of Twitter’s machine learning, ethics, transparency and accountability team, called it a “what, why not” in an interview with tech news website Protocol.
Since 2016, people on Twitter have been able to choose between viewing the first algorithmically-ordered post in the home timeline or viewing the most recent tweets in reverse-chronological order.
Twitter found that tweets about political content from elected officials, regardless of party or whether the party is in power, are algorithmically amplified on the home timeline compared to political content on the reverse-chronological timeline.
The first setting displays a stream of Tweets from accounts that the account holder has chosen to follow, as well as recommendations of other content that Twitter thinks the person might be interested in based on their list of existing people. , which they follow.
Group effects did not translate into individual effects, Twitter said, because party affiliation or ideology is not a factor that the network’s systems consider when recommending content to users.
Therefore, “two individuals in the same political party will not see the same amplification” – said Twitter.
Twitter wrote on its blog: “As a result, what a person sees on their home timeline is a function of how they interact with the algorithmic system, as well as how the system is designed.”
It said it hopes its findings will “contribute to an evidence-based discussion of the role of these algorithms in shaping the consumption of political content on the Internet.”
Twitter argues that “algorithmic amplification is not problematic by default” because “all algorithms are amplified”, but it would be an issue if “preferential treatment as people interact with how algorithms are constructed”. it happens.
The company said it is ready to share the aggregated dataset used in the study to third-party researchers “on request.”
Credit: www.independent.co.uk /