Detecting Misinformation in Photos Utilizing Reverse Image Search

The explosive growth of social networks this decade has significantly impacted society, with digital technologies enabling anyone to create and disseminate fake news using simple editing tools. Media professionals and fact-checkers are now tasked with the complex challenge of verifying visual content, as both multimedia and associated text can be fabricated. Fact-checkers must thoroughly search for related information, such as the time and place of an image's capture, to uncover inconsistencies for content verification. This process demands expertise in journalism and image analysis and involves navigating vast information spaces with current computational and search tools. While AI can tackle specific tasks, it cannot yet replicate human reasoning and judgment. Our study aims to develop a comprehensive pipeline that employs computer science techniques to assist fact-checkers in working more efficiently and effectively, integrating advanced search tools, deep learning models, and additional data like weather conditions to streamline the verification process.