The “fake news” phenomenon may have captured the imagination of Americans during the 2016 presidential campaign and the subsequent investigation of Russia’s attempts to change Donald Trump’s election using fake news on Facebook, among other schemes.
The truth is that fake or fake news has been around as a tool for a while and by many to spread conspiracy theories and propaganda for many years before the 2016 election. Websites including InfoWars and Brietbart among others have been spreading fake news that supports their agendas.
However, it has become a political and social problem since the elections and poor Facebook has become the symbol of the websites that fell for the trap.
Recently, the social media company has admitted its mistakes and has tried to make things right with its subscribers. You are now flagging fake news articles going to Facebook members through your news feed. It is using AI to achieve this.
The company is using AI to identify words or phrases that could mean an item is actually fake. The data for this task is based on articles that Facebook members have individually flagged as fake stories.
Technology currently uses four methods to detect fake news. They include:
- Scoring of web pages. The first to use this technique was Google. Use facts to create a score for websites. Obviously, rating websites is an act in progress. However, as Google has been doing, the technology has grown significantly.
- weight data. This method uses natural language processing engines to review the topic of stories. AI using other models finds out if other sites are reporting the same facts.
- Predict reputation. This technique is based on artificial intelligence that uses predictive analytics and machine learning to forecast the reputation of websites by considering a number of characteristics, including domain name and Alexa web ranking.
- Discover Sensational Words. Fake news advocates have used sensational headlines to capture the interest of a potential audience. This technique uncovers and flags fake news headlines using keyword analysis.
The actual detection of these types of items by AI is a difficult task. Of course, big data analytics is involved, but it also refers to the veracity of the data. Identifying it is really involved with determining the truth of the data. This can be done using the weight of facts method. What happens if a fake news article appears on hundreds of websites at the same time? Under this circumstance, the use of weighing the facts technique may cause AI to determine that the story is legitimate. Perhaps using the method of predicting reputation along with weighing the facts can help, but there could still be problems. For example, trusted news source websites that don’t take the time to verify a story might pick it up on the assumption that it’s true.
It is obvious that the use of AI to identify these items needs further development. Various organizations are involved in improving AI capability. One such establishment that is involved is West Virginia University.
The Reed College of Media, in cooperation with West Virginia University’s Benjamin M. Statler College of Engineering and Mineral Resources, has created a course that focuses on using AI to identify fake news articles.
Seniors taking a computer science elective are working in teams to develop and implement their own AI programs and are also involved in the project.
Another group known as the Fake News Challenge is also looking for a way for AI to successfully combat fake news. It is a grassroots organization of more than 100 volunteers and 71 teams from academia and industry to tackle the problem of fake news. It is developing tools to help people check the facts and identify fake news.
As organizations work to improve the AI for finding these stories, a variety of tools are available to deal them a blow. These include:
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Spike, which identifies and predicts viral and breakout stories, and uses big data to predict what will drive engagement.
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Hoaxy, which is a tool that helps users identify fake news websites.
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Snoopey, which is a website that helps identify fake news articles.
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CrowdTangle, which is a tool that helps monitor social content.
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Meedan, which is a tool that helps check breaking news online.
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Google Trends, which monitors searches.
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La Decodes de Le Monde, which is a database of fake news and real news websites.
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Pheme, which is a tool that verifies the veracity of online and user-generated content.
