Publication Date
6-5-2023
Document Type
Conference Proceeding
Publication Title
2023 IEEE Conference on Artificial Intelligence (CAI)
DOI
10.1109/CAI54212.2023.00099
Abstract
Misinformation is still a major societal problem. The arrival of ChatGPT only added to the problem. This paper analyzes misinformation in the form of text from a spectral analysis perspective to find the answer to why the problem is still unsolved despite multiple years of research and a plethora of solutions in the literature. A variety of embedding techniques are used to represent information for the purpose. The diverse spectral methods used on these embeddings include t-distributed Stochastic Neighbor Embedding (t-SNE) and Principal Component Analysis (PCA). The analysis shows that misinformation is quite closely intertwined with genuine information and the machine learning algorithms are not as effective in separating the two despite the claims in the literature.
Department
Applied Data Science
Recommended Citation
Vishnu S. Pendyala and Foroozan Sadat Akhavan Tabatabaii. "Spectral analysis perspective of why misinformation containment is still an unsolved problem" 2023 IEEE Conference on Artificial Intelligence (CAI) (2023). https://doi.org/10.1109/CAI54212.2023.00099
Comments
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