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 flip the election for Donald Trump using fake news on Facebook, among other stratagems.

The truth is that fake news or fake news was used for some time as a tool to disseminate propaganda and conspiracy theories for many years before the 2016 election. Websites, including InfoWars and Brietbart, enter others, have broadcast fake news that supports their agendas.

However, it has become a political and societal issue since the election and poor Facebook has become the poster child for websites that have fallen for the trap.

Recently, the social media company admitted its mistakes and tried to get it right with its followers. He is now reporting fake news articles that are sent 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 actually a fake. The data for this task is based on the articles that Facebook members individually reported as being fake stories.

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

  • Rate 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 tremendously.
  • Weigh the facts. This method uses natural language processing engines to examine the subject matter 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. Proponents of fake news have used sensational headlines to grab the interest of a potential audience. This technique finds and flags fake news 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. Maybe using the reputation prediction method in conjunction with fact finding can help, but there could still be issues. For example, websites of reliable news sources that don’t take the time to check out a news item might pick it up assuming it is true.

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

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

Senior students taking an elective course in computer science working 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 local 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 work on improving the AI ​​to find these stories, there are a variety of tools available to strike a blow at them. These include:

  • Spike, which identifies and predicts breakup and viral stories 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 identifies fake news articles.

  • CrowdTangle, which is a tool that helps monitor social content.

  • Meedan, which is a tool for checking the latest news online.

  • Google Trends, which monitors searches.

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

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

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