Sign In

Communications of the ACM

Research highlights

Technical Perspective: Leveraging Social Context for Fake News Detection

man with newspapers and a sign for a true-false crossroads, illustration

As social media emerged as a key source of information, malicious users started to manipulate social platforms to their own ends. Today, online disinformation efforts (so-called infodemics) are routinely plaguing public debates, political events, and information campaigns alike. Detecting fake news via online social media has become a central issue, fostering an arms race between malicious users and platform operators.

To this day, two broad strategies have been developed to automatically detect disinformation campaigns on online media: analyzing the information content—leveraging natural language processing techniques3 or authoritative information sources—or analyzing its context, for example by exploring the interplay between end users, publishers, and news pieces.5 In the following paper, the authors focus on the latter strategy by introducing a new graph-based, contextual technique for fake news detection. Their approach is based on two main pillars: a structurally rich graph representation of social context on one hand, and a dedicated learning framework leveraging an inductive approach to graph representation learning on the other hand.


No entries found

Log in to Read the Full Article

Sign In

Sign in using your ACM Web Account username and password to access premium content if you are an ACM member, Communications subscriber or Digital Library subscriber.

Need Access?

Please select one of the options below for access to premium content and features.

Create a Web Account

If you are already an ACM member, Communications subscriber, or Digital Library subscriber, please set up a web account to access premium content on this site.

Join the ACM

Become a member to take full advantage of ACM's outstanding computing information resources, networking opportunities, and other benefits.

Subscribe to Communications of the ACM Magazine

Get full access to 50+ years of CACM content and receive the print version of the magazine monthly.

Purchase the Article

Non-members can purchase this article or a copy of the magazine in which it appears.
Sign In for Full Access
» Forgot Password? » Create an ACM Web Account