Artificial Intelligence Techniques to Restrain Fake Information
Lecture Notes in Networks and Systems, ISSN: 2367-3389, Vol: 473, Page: 665-673
2023
- 10Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures10
- Readers10
- 10
Conference Paper Description
In the current world, there has been an upsurge in the use of social networking sites like Facebook, WhatsApp, Twitter, etc. These are considered suitable sites for the exchange of messages and sharing pictures and videos. Besides providing entertainment to the users, sometimes the information circulating on these platforms may be fake or misleading. In this chapter, we reviewed the literature on AI technologies that address the issue of fake news detection, the process of information flow, different data sets to detect fake news, and future perspectives to improve the credibility of information.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85140444564&origin=inward; http://dx.doi.org/10.1007/978-981-19-2821-5_56; https://link.springer.com/10.1007/978-981-19-2821-5_56; https://dx.doi.org/10.1007/978-981-19-2821-5_56; https://link.springer.com/chapter/10.1007/978-981-19-2821-5_56
Springer Science and Business Media LLC
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