Bring your excellent programming skills and hard-wroking attitude to help identify misinformation across multimodal content.
Fake news has altered society in negative ways in politics and culture. It has adversely affected both online social network systems as well as offline communities and conversations. Using automatic machine learning classification models is an efficient way to combat the widespread dissemination of fake news. While research in the area of fake news detection is of high importance for society, most of the existing methods opt for uni-mode approaches, as analyzing multimodal content is often more complicated and the availability of a reasonably sized dataset poses extra challenges.
In this project, we focus on a threat scenario where an image is misused to support a certain narrative expressed in a caption. While none of the content components may be manipulated, but the semantic context they represent together is manipulated/inconsistent.
Students will contribute to a formal research publication.
|Length of commitment||About 6-9 months|
|In-person, remote, or hybrid?||Hybrid|
|Level of collaboration||Individual project|
|Benefits||Research experience; academic credit|
|Who is eligible||Juniors and seniors with Python programming skills and who have taken courses in machine learning/AI|
The specific preparation activities for this project will be customized through discussions between you and your project mentor. Please be sure to ask them for the instructions to complete the required preparation activities.
Computer Science & Engineering