Analyzing traffic from the The Gateway Pundit, a popular far-right website known for repeatedly sharing false information, we find that search engines and social media platforms are the main drivers of traffic and the site is more popular in counties that voted for Trump in 2020.
Chen, Zhouhan, Haohan Chen, Juliana Freire, Jonathan Nagler, and Joshua A. Tucker. "What We Learned About The Gateway Pundit from its Own Web Traffic Data." Workshop Proceedings of the 16th International AAAI Conference on Web and Social Media, (2022). https://doi.org/10.36190/2022.68
Jun 01, 2022
Area of Study
To mitigate the spread of false news, researchers need to understand who visits low-quality news sites, what brings people to those sites, and what content they prefer to consume. Due to challenges in observing most direct website traffic, existing research primarily relies on alternative data sources, such as engagement signals from social media posts. However, such signals are at best only proxies for actual website visits. During an audit of far-right news websites, we discovered that The Gateway Pundit (TGP) has made its web traffic data publicly available, giving us a rare opportunity to understand what news pages people actually visit. We collected 68 million web traffic visits to the site over a one-month period and analyzed how people consume news via multiple features. Our referral analysis shows that search engines and social media platforms are the main drivers of traffic; our geo-location analysis reveals that TGP is more popular in counties where more people voted for Trump in 2020. In terms of content, topics related to 2020 US presidential election and 2021 US capital riot have the highest average number of visits. We also use these data to quantify to what degree social media engagement signals correlate with actual web visit counts. To do so, we collect Facebook and Twitter posts with URLs from TGP during the same time period. We show that all engagement signals positively correlate with web visit counts, but with varying correlation strengths. For example, total interaction on Facebook correlates better than Twitter retweet count. Our insights can also help researchers choose the right metrics when they measure the impact of news URLs on social media.