Linda Abelman is an 18-year-old Stoke Newington resident who has just exercised her right to vote for the first time in the December election. Having spent the past three years confused by Brexit, Linda decided to conduct comprehensive research before deciding on a candidate. In true Generation Z fashion, she took to YouTube. When I asked her what she found, I was expecting her to tell me about her pro-Labour agenda. I assumed that YouTube’s algorithms would provide her with content that was popular to the youth of London, such as herself. But her answer was nothing like that. Instead, she filled me in about the overwhelming amount of anti-Semitism claims that plagued her perception of Jeremy Corbyn; and therefore, the Labour Party. Because my assumption was so off, I decided to investigate YouTube’s recommendation algorithm further by examining the video network that enables anti-Semitism claims surrounding Jeremy Corbyn.
YouTube’s recommendation algorithms are designed to increase the time people spend over the platform. This is necessary for its aggregation of revenue from advertising companies. After Google Brain, the company’s AI division, took over YouTube’s recommendations in 2015, the algorithm seemed to produce more extreme suggestions. According to Zeynep Tufekci, an associate professor at the University of North Carolina, the algorithm “promotes, recommends and disseminates videos in a manner that appears to constantly up the stakes.”. This means that more intense content is made instantaneously available. Former YouTube employee, Guillaume Chaslot claims that the demand for user watch time saw the algorithm push conspiracy videos on users. He believes increased efforts to grasp user attention will only spread problematic and prohibited content. His project to introduce diversity to the recommendations algorithm did not stimulate the same watch time and was therefore, shut down. Not only does this show YouTube’s blinding determination for more watch time, but also its power as an instrument for radicalisation. This limits the younger generation, like Linda, who rely on YouTube for their understanding of the world around them.
To understand Linda’s experience, I conducted a network analysis of YouTube videos related to Jeremy Corbyn and anti-Semitism claims. The study attempted three main objectives to understand the narrative imposed. First, to utilise Gephi for data visualisation. Second, to identify the central clusters that contribute to content analysis. Third, to isolate the unexpected clusters that raise concern within the network.
The above graph shows a cluster of nodes that exhibit two central themes: the reaction of the Jewish community to anti-Semitism claims and the general election.
The blue arrows point to videos that address Corbyn’s perspective on Judaism. The video “Jews are terrified of a Corbyn government” is a central node. This video contributes to the Jewish community’s narrative on Corbyn with 87% of British Jews viewing Corbyn as anti-Semitic. The video confirming the Chief Rabbi’s attack of the Labour party only furthers this disposition, where he declared that a “new poison” of anti-Semitism existed at the top. The small community of British Jews, only 0.5 of the population, look towards the Rabbi as a guide for their best interests. The video on the Rabbi is directly connected to Boris Johnson’s response. This shows the highly-politicised nature of the issue that feeds into the recommendation algorithm. Johnson’s reaction creates a divide between the two parties that furthers the anti-Semitic narrative behind the Labour party. Corbyn finally addresses this in a connected video; however, this is drowned out by more controversies that link him to anti-Semitism. Therefore, this series of related videos solidify anti-Semitic claims surrounding Jeremy Corbyn.
The yellow arrows demonstrate videos that attach the general election to allegations against Corbyn. Each party’s manifestos are brought to light with the topic of Brexit as the main concentration. The BBC’s video “Johnson V Corbyn election debate: Who? Parties react” shows a reputable news source contribute to the divide between the two parties.
This focus of Brexit contributes to the algorithms facilitation of controversy. People, like Linda, who were searching the general election and Brexit to educate themselves instead came across polarising information on both parties. Not only does this negatively affect the political process by shying away from facts, but it also degrades candidates for reasons other than their policies. This is harmful to the general public because it prohibits them from fully utilising their political power. While the connected node “What would Boris Johnson and Jeremy Corbyn get each other for Christmas” is not directly affiliated with anti-Semitic claims against Corbyn, it does provide a narrative on each leader’s personality. This is extremely powerful within elections because it shapes a candidates’ likeability. The YouTube recommendation algorithm’s ability to combine the controversial and personal makes it a notable force within the political process.
Graph B shows the isolated outliers that do not contribute to the narrative. “I bought CELEBRITY S used Iphone/ now I KNOW his SECRET” is an animated video that involves a young girl talking about knowing Justin Bieber’s secrets. The keywords “secret” and “scandal” are used within this video. “I broke my legs to satisfy my mom but it was not enough” also contains the keywords “accusation” and “scandal”, which perpetuates the extreme content that excites users.
My brief investigation calls for increased awareness over radicalised YouTube suggestions. The political process is in the hands of people like Linda, who are increasingly making life-altering decisions based on this content.