PageRank Post
Can algorithms really tackle the fake news fiasco?
http://www.computerworld.in/feature/can-algorithms-really-tackle-fake-news-fiasco
The study published by the University of Oxford pegs the 2016 US presidential election as a “watershed moment” that sees social media manipulation at its worst. Both Trump and Clinton camps exploited big data to manipulate public opinion. This phenomenon is happening right now and is not just limited to the election. Many companies are trying to avoid this phenomenon by creating AI-based algorithms. In order to keep the fake news from reaching the top of the web search, companies are in need of updating their AI-based algorithms.
Before going into the individual companies’ algorithm regarding fake news, it is important to understand the concept of PageRank.PageRank is a value assigned to a web page as a measure of its popularity or importance. PageRank is used to determine the order in which search engine results are presented. PageRank is the dominant mode of endorsement; for instance, a page is ranked high if it is cited by other important pages.
Google is one of the leading companies that try to combat fake news. Its PageRank algorithm ranks the search results based on the pages that are linked to the publication. Because PageRank applies across multiple platforms, we can identify fake news from real.
Unlike most cases where AI is more dependable, in the case of combating fake news, human intervention is reliable because algorithms can be easily manipulated and cannot make complex editorial decisions. Thus, companies that deal with big data should develop a better algorithm for their PageRank system. Also, big companies such as facebook are investing money to hire to train the algorithm. Another way to zero in on fake news is Google’s reverse image search. Users can upload the image or photograph in question and Google can pinpoint the source of the image.