Communications of the ACM
CR Researchers Take p Fight Against Fake News
Researchers in the University of California, Riversides Multi-Aspect Data Lab, are developing novel data science techniques to address a variety of problems in social network analysis.
Credit: UCR Today
Researchers at the University of California, Riverside (UCR) are developing ways to address problems in social network analysis, including dissemination of malicious misinformation.
"Our work aims at the early detection of such articles, especially in cases where we have no external knowledge regarding the validity and veracity of any article," says UCR professor Evangelos E. Papalexakis.
The team analyzes social groups in which all interacting members connect by recording, examining, categorizing, and modeling inputs based on tensor decompositions. All multi-aspects are digitally rendered as multidimensional cubes so the system can investigate and "comprehend" what is actually occurring, grading the news' veracity.
"The...techniques...capture nuanced patterns that successfully identify different categories of fake news, without using any external knowledge about the validity of any particular article," Papalexakis says.
The researchers' work was presented last month at the 11th ACM International Conference on Web Search and Data Mining (WSDM 2018) in Los Angeles, CA.
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