Google Snippets and Twitter Posts; Examining Similarities to Identify Misinformation

Despite numerous efforts to address the persistent issue of fake news, its proliferation continues due to the vast volume of information circulating on social media platforms. This poses a significant challenge to manual fact-checking processes. To explore a potential solution, this study investigates the applicability of Google search and its results as a practical tool for detecting fake news on platforms like Twitter. The research focuses explicitly on comparing Google search result snippets with tweets to assess their similarity and determine if such similarity can serve as an indicator of misinformation. However, the study reveals that the observed similarity between tweets and snippets does not necessarily correlate with news credibility. Consequently, alternative techniques, such as retrieving complete news articles and assessing sources, may be necessary to effectively tackle the challenge of fake news detection on social media. This research spots light on the limitations of relying solely on snippet similarity. In addition, it suggests the importance of considering comprehensive content analysis and source credibility in future works to combat misinformation.