Misinformation is a term used to describe false or inaccurate information that can be found on social media platforms. This article focuses on content-based methods for detecting misinformation, as opposed to other approaches that consider the circumstances surrounding the content. The authors define misinformation and its subtypes, and outline different groups of misinformation detection models. They also discuss the concept of drift and its application to misinformation detection in the South African context.
Key points
- Misinformation is false or inaccurate information found on social media
- Content-based methods are used to detect misinformation
- Misinformation can be divided into subtypes, such as lies by omission and lies of commission
- Different groups of misinformation detection models exist, including multimodal and natural language processing models
- Concept drift applies to misinformation detection in the South African context
In simple terms, misinformation is like a puzzle with missing pieces. Some pieces might be false or inaccurate, while others are accurate. Content-based methods are like a special tool that helps detectives (researchers) find and fix the missing pieces of the puzzle to get a clear picture of what’s really going on. There are different groups of tools, each with their own unique abilities, like multimodal models that can analyze both text and images, or natural language processing models that can understand the meaning behind words. These tools help detectives keep up with changes in the puzzle (concept drift), so they can continue to identify misinformation accurately. In the South African context, these tools are particularly useful for identifying misinformation on social media platforms.
