This study analyses website traffic to websites known for publishing fake news preceding the 2016 US Presidential elections. It uses 114 days of combined data from two popular desktop web browsers: Internet Explorer 11 and Edge. The analysis began on July 18th, 2016 (the start of the Republican national convention) and ended on November 8th, 2016 (election day). This study contributes the body of academic and journalistic work on this subject through a fine-grained geographic and temporal perspective.
Highlights:
- The study confirmed that social media (Facebook and Twitter) was the primary source for the circulation of fake news stories. These sites accounted for 68% of all page visits for which traffic sources could be determined. The analysis also revealed that visits to fake news sites were relatively rare.
- Secondly, the study found two temporal patterns of the stories stories that were short-lived which received most of their views in 24-48 hours, and stories that persisted for longer periods of time and steadily acquired views. The findings also observe the strong role of social in the exposure of long-lived stories.
- The research finds a correlation between the average daily traffic of users visiting fake news websites with the geographic voting patterns at the state level. States or countries with higher traffic to fake news sites also tended to vote for Donald Trump.