Can the Hawkes process be used to evaluate the spread of online information?

Abstract

Social media allows people to easily express themselves and spread information online. This is a boon to self-expression and communication but has allowed for misinformation to flourish as well. It may be difficult to differentiate facts from misleading opinions. Automatic fact-checking has the potential to reduce the spread of misinformation while browsing. Multiple potential approaches to implementing fact-checking software have been explored. One approach is to detect the information’s origin and evaluate if it is a valid primary source. Most existing methods to model the spread of information online require extensive computational resources and time to train a deep-learning algorithm, as well as a high-level representation of the propagation of the content. In addition, these methods are mainly used to classify and verify the information itself rather than the information’s provenance. The Hawkes process makes it possible to evaluate and model information spread tendencies and map out the source of the information by comparing the intensity of shared posts over time. 1000 posts of 3 blog pages on Reddit were scraped from the Internet to test if the modified Hawkes process can detect which page is influenced by which. The Hawkes process was able to distinguish the influenced, the influencer and the control blog page. Therefore, the Hawkes process may be used to identify the primary sources of information. Future research may need to compare the accuracy and precision of this process compared to other methods.