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- W4316659640 abstract "In modern era, social bots have become more prevalent as automated social actors as a result of the growth of services on web and fame of online social networks (OSN). Social media sites such as Facebook, YouTube, Twitter, Telegram, LinkedIn, etc. are populated with enormous numbers of “social bots”. “Social bots” can be typically believed of as artificial social media accounts used by bad actors to sway public opinion. They are praised for having the capacity to connect with human users and create content on their own. These players can take on a variety of harmful activities, such as eavesdroppers on people's conversations, con artists, spoofers, disseminators of false information, manipulators of the stock market, astroturfers, and content scavengers (spammers, spreaders of malware, etc.). Therefore, the study describes the possible risks posed by harmful social bots, evaluates detection methods using a methodological classification, various available data sources and suggests directions for future study. The findings can assist OSN managers and researchers in comprehending the potentially harmful effects of harmful social bots and can strengthen the current countermeasures." @default.
- W4316659640 created "2023-01-17" @default.
- W4316659640 creator A5058168844 @default.
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- W4316659640 date "2022-11-24" @default.
- W4316659640 modified "2023-09-30" @default.
- W4316659640 title "A Comprehensive Review on Social Botnet Detection Techniques" @default.
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- W4316659640 doi "https://doi.org/10.1109/icaiss55157.2022.10010877" @default.
- W4316659640 hasPublicationYear "2022" @default.
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