According to a Rutgers study, political ideology and user choice, rather than algorithmic curation, have the most significant impact on engagement with partisan and unreliable news on Google Search. The study aimed to address concerns surrounding digital algorithms that tend to learn from user preferences and present information that aligns with users’ attitudes and biases.
However, the researchers discovered that search results displayed to Democrats do not significantly differ in terms of ideology from those shown to Republicans. The variations in ideological content become apparent when individuals themselves decide which search results to click on or which websites to visit.
The findings also indicate that the proportion of low-quality content presented to users does not differ significantly among different partisan groups. However, certain demographics, particularly older participants who identify as ‘strong Republicans,’ are more likely to engage with such content.
User Choice & Political Bias on Google Search
“Google’s algorithms do sometimes generate results that are polarizing and potentially dangerous. But what our findings suggest is that Google is surfacing this content evenly among users with different political views,” the researchers explain. “To the extent that people are engaging with those websites, that’s based largely on personal political outlook.”
Despite the significant influence algorithms wield over individuals’ news consumption, only limited research has focused on web search, with even fewer studies examining exposure (referring to the links displayed in search results), follows (the links users choose to visit from search results), and engagement (all the websites users explore while browsing the web).
One of the challenges has been measuring user activity accurately. Tracking website visits necessitates access to users’ computers, leading researchers to rely primarily on theoretical approaches to speculate about how algorithms contribute to polarization or guide individuals into political “filter bubbles” and “echo chambers.”
Echo Chambers & Filter Bubbles: Algorithmic Impact
To bridge these knowledge gaps, the authors conducted a two-wave study, combining survey responses with empirical data obtained through a custom browser extension designed to measure exposure and engagement with online content during the 2018 and 2020 U.S. elections.
A total of 1,021 participants voluntarily installed the browser extension on Chrome and Firefox. This software recorded the URLs of Google Search results, along with Google and browser histories, providing researchers with precise information about the content users interacted with and the duration of their engagement.
Additionally, participants completed a survey where they self-reported their political identification on a seven-point scale, ranging from “strong Democrat” to “strong Republican.”
User Control: Driving News Engagement
The findings from both waves of the study indicated that an individual’s political identification had limited influence on the quantity of partisan and unreliable news they were exposed to on Google Search. However, a clear relationship emerged between political identification and engagement with polarizing content.
Platforms like Google, Facebook, and Twitter operate as technological black boxes, where researchers are aware of the input and can measure the output, but the algorithms responsible for curating the results remain proprietary and rarely face public scrutiny. Consequently, many attribute the creation of echo chambers and filter bubbles to the technology employed by these platforms, as they systematically expose users to content that aligns with and reinforces their existing beliefs.
“This doesn’t let platforms like Google off the hook,” the researchers conclude. “They’re still showing people information that’s partisan and unreliable. But our study underscores that it is content consumers who are in the driver’s seat.”
