Can AI fight fake news?


The phenomenon of ‘fake news’ may have captured the imagination of Americans during the 2016 presidential campaign and subsequent investigation into Russia’s attempts to tip the election to Donald Trump using fake news on Facebook among other ploys.

The truth is that fake news or fake news has been around for quite some time and by many to spread propaganda and conspiracy theories for many years ahead of the 2016 election. Websites such as InfoWars and Brietbart, among others , broadcast fake news that supports their programs.

However, it has become a political and societal issue since the election and poor Facebook has become the model for websites that have fallen into the system.

Recently, the social media company admitted its mistakes and tried to get it right with its followers. It now flags bogus news articles that go to Facebook members through their News Feed. He uses AI to achieve this.

The company uses AI to identify words or phrases that could mean that an article is in fact a fake. The data for this task is based on the articles that individual Facebook members have reported as fake stories.

Technology currently uses four methods to spot fake news. They include:

  • Note the web pages. The first to use this technique was Google. It uses facts to create a score for websites. Obviously, website rating is a work in progress. Yet, as Google has done, the technology has developed considerably.
  • Weigh the facts. This method uses natural language processing engines to examine the subject of the stories. AI using other models finds out if other sites are reporting the same facts.
  • Predict reputation. This technique is based on AI using predictive analytics and machine learning to forecast website reputation taking into account a number of features including domain name and Alexa web ranking.
  • Discover sensational words. Fake news supporters have used sensational headlines to grab the attention of a potential audience. This technique uncovers and reports false headlines using keyword analysis.

The actual detection of these types of items by AI is a difficult undertaking. Of course, big data analysis is involved, but it is also about the veracity of the data. Identifying it is actually involved in determining the veracity of the data. This can be done using the factual weighting method. What if a fake news article appears on hundreds of websites at the same time? Under these circumstances, using the fact-weighing technique can cause the AI ​​to determine that the story is legitimate. Perhaps using the reputation prediction method in conjunction with factual weighting can help, but there could still be issues. For example, websites of reliable news sources that don’t take the time to verify a story might pick up on it assuming it’s true.

It is evident that the use of AI to identify these articles requires further development. A number of organizations are involved in improving AI capabilities. One of those institutions that is involved is West Virginia University.

The Reed College of Media, in cooperation with the Benjamin M. Statler College of Engineering and Mineral Resources at West Virginia University, has created a course focused on using AI to identify bogus news articles.

Senior students taking an optional computer science course work as a team to develop and implement their own AI programs are also involved in the project.

Another group known as the Fake News Challenge is also looking for a way for AI to successfully tackle fake news. It is a grassroots organization of over 100 volunteers and 71 teams from academia and industry to tackle the problem of fake news. He is developing tools to help people check the facts and identify fake news.

As organizations strive to improve the AI ​​to find these stories, there are a variety of tools available to strike a blow at them. These include:

  • Spike, who identifies and predicts stories of breaches and virals and uses big data to predict what will drive engagement.

  • Hoaxy, which is a tool that helps users identify fake news websites.

  • Snoopey, which is a website that helps identify bogus news articles.

  • CrowdTangle, which is a tool for monitoring social content.

  • Meedan, which is an online news checking tool.

  • Google Trends, which monitors searches.

  • The Decodes From Le Monde, which is a database of fake news and real news sites.

  • Pheme, which is a tool that checks the veracity of user-generated and online content.


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