Optimal Search Strategy for Research on Misinformation and Fake News: A Comparison between Search Systems and Keyword Choices

Abstract

This paper explored the issue of identifying the right keyword and search engine or database to help communication scholars gain optimal experience and obtain the best outcomes in literature searches on the topic of misinformation and fake news. Five major types of electronic search systems were evaluated for their precision (relevancy), recall (sensitivity), and duplication rates. They included discovery layers such as Summon, web crawlers such as Google Scholar, library databases such as EBSCO Academic Search Complete, Journal publisher website search, and specialized journals using 14 keywords to search for the same topic. Based on the findings, Summon and HKS Misinformation Review had the highest relevancy ratings. It was notable that Google Scholar only ranked 6^th of the 14 keywords analyzed. The two main keywords ̶ misinformation’ and ‘fake news’ had a lower relevancy rating compared to the other keywords like ‘infodemic’ and ‘news propagation’ which had the highest relevancy scores. The lack of overlap in listing using different keywords and different search systems demonstrated that there was no single all inclusive, top search engine and that using a variety of terms and different search systems was necessary to conduct a thorough literature review on the subject. The study’s findings and their implications for conducting literature searches by researchers in the Global North and the Global South were also discussed.