The Sourcer content-labeling algorithm helps people get insight faster into what they are reading and be protected against fake news.
We recognized that there are a lot of issues around how people currently consume news. It is difficult for a person to determine whether something is true or credible because information about a given topic can be found on many different channels and from many different sources. Furthermore, readers are lacking insights and information to be able to critically evaluate the credibility of what they are reading. To get an idea about the size of the problem of fake news, it is costing the global economy $78 billion per year.
We, at Sourcer, are building an algorithm that will give people more insights into the news they consume. Users can get information using a browser extension or having it integrated into an existing product, like Facebook or Twitter. Our algorithm can analyze the stance of an article, quickly find similar posts about the same topic, and this way users can easily navigate different opinions and get insight faster. This can be combined with other features like source credibility and this information can be presented to the user.