A. Sneha, U. Leenasri, V. Anusha, S. Shirisha, AI “, Article Info
{"title":"AI Based Detecting Deception in Online Interactions: An Analysis of the Dishonest Internet Users","authors":"A. Sneha, U. Leenasri, V. Anusha, S. Shirisha, AI “, Article Info","doi":"10.46243/jst.2024.v9.i1.pp39-49","DOIUrl":null,"url":null,"abstract":"With the widespread adoption of the internet, online interactions have become an integral part of modern communication. However, this surge in digital interactions has also brought about a significant rise in deceptive practices, ranging from misinformation and fraud to identity theft and cyberbullying. Detecting and mitigating these dishonest behaviors has become a critical concern for maintaining trust and integrity in digital communities. The primary challenge lies in developing a robust and automated system capable of identifying deceptive content amidst the vast volume of online interactions. In the absence of advanced AI-based systems, deception detection in online interactions has heavily relied on manual monitoring, keyword-based filters","PeriodicalId":17073,"journal":{"name":"Journal of Science and Technology","volume":"17 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46243/jst.2024.v9.i1.pp39-49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the widespread adoption of the internet, online interactions have become an integral part of modern communication. However, this surge in digital interactions has also brought about a significant rise in deceptive practices, ranging from misinformation and fraud to identity theft and cyberbullying. Detecting and mitigating these dishonest behaviors has become a critical concern for maintaining trust and integrity in digital communities. The primary challenge lies in developing a robust and automated system capable of identifying deceptive content amidst the vast volume of online interactions. In the absence of advanced AI-based systems, deception detection in online interactions has heavily relied on manual monitoring, keyword-based filters