Date of Award
Thesis - SCU Access Only
Santa Clara : Santa Clara University, 2018.
With the continuous growth of digital news, it can be difficult to differentiate facts from false claims among thousands of available news sources. Naturally, this leads to the spread of misinformation from poorly informed news readers. Current solutions validate news sources but can still be biased themselves. Others however, rely on people to do the research and write articles or summaries and inherently take up longer than desired. Our solution is a web application, News Breaking, that scrapes the web for news articles on a current event, compares them against each other to identify claims likely to be true, and presents a succinct, fact-based summary to the reader.
Morales, Esai; Tudor, Nathan; and Velcich, Kevin, "News Breaking: Fake News Detection and Facts Summarization" (2018). Computer Science and Engineering Senior Theses. 113.