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Google Algorithm ‘Failed Spectacularly’ During Las Vegas Shooting


On October 10, 2017, Stephen Paddock opened fire on thousands of people at the Route 91 Country Music Festival from his 32nd floor suite in the Mandalay Bay hotel in Paradise, Nevada; but that is not the information Google was spreading early in the investigation. According to the article, “Google Algorithm ‘Failed Spectacularly’ During Las Vegas Shooting, Google News Creator Says”, by Benjamin Fearnow from the International Business Time, the algorithm Google uses to push news articles to their “Top Stories” page had failed and put a fake news article from, claiming another man as the shooter. Wired, a news outlet that Fearnow cites in his article contacted Krishna Bharat, a former employee that had worked on Google News, and he was appalled by the mistake the algorithm had made. Fearnow explains how Google News’ “Top Stories” page works to find the most relevant and correct information from trusted news sources to help people find information more quickly. The program is engineered in a way that it validated news sources by the accuracy of their previous articles, “if a source was caught faking the news it was out”, said Bharat. Unfortunately, about four years ago Google news had loosened the strict vetting policy a few years ago, one reason why the article slipped through the cracks.


When introduced to the “Web Search” in the class, the topic of Google’s suggested sites and relevant pages at the top of the search results was discussed at length. When giving these suggestions that Google gives their users, the site has to deal with the problem of scarcity (having only one document to solve the searcher’s problem) and the problem of abundance (having too many documents and filtering out the most relevant ones). With the case of the Las Vegas Shooting fake news article, the algorithm Google uses was dealing with the problem of abundance, trying to sort through thousands of news articles about the shooting and put the best ones at the top. The problem was that as more people clicked on the article, it got stronger and spread more quickly. In the end, the algorithm did not fix itself and there proved to be a major flaw in the system. Moving forward, this example of the “Top Stories” from Google, exemplifies the importance of the ranking of web search results and the suggested pages, two devices that can be explained by page rank and page strength, a topic thoroughly covered in Networks at Cornell University.


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October 2017