As the Internet becomes more sophisticated with more platforms to share information and opinions, so does its usage to spread misinformation or fake news. Fortunately, tools are available to help you identify and shut down fake news or other misinformation.
In this post, we’ll take a look at how real-time analytics and AI-driven machine learning can be used to identify fake news.
What is Fake News?
Fake news is any information presented as fact but is false or misleading. This content often contains political agendas or propaganda meant to misinform readers about current events or public figures.
Fake news has been around since the invention of the printing press, but it has become an especially prevalent issue in recent years due to the rise of social networking sites such as Facebook and Twitter, where people can easily share stories without fact-checking or verifying validity.
Fake news is an epidemic that has affected our lifestyles and opinions and even influenced our political views. Nowadays, finding a topic that hasn’t been affected by fake news at some point is hard. And, it’s essential that we take steps towards identifying fake news before it becomes more of a destructive force that spreads too far into our lives.
Why should businesses worry about Fake News?
Image source – https://techonomy.com/fake-news-business-crisis/
As an example of fake news, a flier circulated on social media, “Starbucks Dreamer Day,” promised 40% off on any menu item for “all undocumented Americans” on August 11, 2017. Many believed it true and spoke against the company for such offers. Starbucks then had to make extra efforts to shut down the rumors. Fake news can damage businesses in many different ways:
- If a company’s reputation is damaged by fake news, it can be difficult to repair. The company may lose sales and customers and face legal action from consumers or shareholders.
- Fake news can also damage your business financially. For example, If you’re running an e-commerce site, fake news can cause you to lose money if you lose sales because of it. If the fake news gets picked up by other media outlets, it could affect your reputation and finances.
- Fake news can hurt your business relationships with vendors and partners. If a vendor or partner is affected by fake news about your company, they may no longer want to work with you or even sue you if they believe the false information caused them damages.
- Fake news affects supply chains because businesses rely on accurate information about their suppliers and customers to make decisions about their operations. If this information is false, organizations may make poor decisions that negatively impact their operations or even put them out of business altogether.
- Finally, fake news can harm employees’ mental health by putting employees at risk for depression or anxiety. For example, suppose an employee reads a story about layoffs at their company. In that case, even though there were no plans to cut staff, they could experience anxiety related to job security.
Combating Fake News With real-time analytics and AI-driven machine learning
Real-time analytics and AI-driven machine learning can help identify fake news in real-time using natural language processing (NLP) and machine learning algorithms to analyze text for known common patterns. Real-time analytics is the process of collecting, analyzing, and interpreting data at the time it occurs. Machine learning then allows computers to learn from the data without being programmed. These powerful technologies can quickly and accurately detect fake news.
The first step is to train an algorithm to tell the difference between real and fake news. This can be done even for image data by combining different machine learning algorithms, such as Convolutional Neural Networks (CNNs) or Recurrent Neural Networks (RNNs). CNNs are effective at identifying specific objects in an image, while RNNs can learn from sequences of images and videos.
Once an algorithm is trained to detect fake news, it can be used to scan user-generated content for any signs of misinformation or fakery. For example, if you want to identify fake news about a brand ‘ABC,’ you could use algorithms to search for keywords like “ABC” or “ABC products,” etc., and then use machine learning algorithms to analyze how these words are clustered together in sentences across different sites related to each topic. If two other sites used similar language patterns but had different domain names, it might indicate suspicious activity.
Facebook uses its machine learning algorithm to identify fake news. The algorithm considers various factors like the number of likes, shares, and comments on an article and its popularity based on the number of people who have read it or liked it. The algorithm also checks if any user has reported an article as false or unreliable by marking it with a “disputed” tag when they share it on their page wall or post it on their timeline. If any user marks an article as disputed, then Facebook removes that article from their News section.
In a blog post, Tessa Lyons, Product Manager, Facebook, writes, “One challenge in fighting misinformation is that it manifests itself differently across content types and countries. To address this, we expanded our test to fact-check photos and videos. This includes those that are manipulated (e.g., a video that is edited to show something that did not really happen) or taken out of context (e.g., a photo from a previous tragedy associated with a different, present-day conflict).”
Tessa further adds, “Machine learning helps us identify duplicates of debunked stories. For example, a fact-checker in France debunked the claim that you can save a person having a stroke by using a needle to prick their finger and draw blood. This allowed us to identify over 20 domains and over 1,400 links spreading that same claim.”
The next step is to identify what makes a particular piece of content fake or false so that we can prevent this from happening again in the future.
If you are interested in learning more about building advanced AI solutions to help combat fake news, email us at email@example.com. We know it’s not just about stopping the spread of misinformation but also building trust in your brand and empowering you to take action on potential issues before they spread.
Intellect Data, Inc. is a software solutions company incorporating data science and artificial intelligence into modern digital products with Intellect2TM. IntellectDataTM develops and implements software, software components, and software as a service (SaaS) for enterprise, desktop, web, mobile, cloud, IoT, wearables, and AR/VR environments. Locate us on the web at www.intellectdata.com.