Taxonomy Goes Digital: Getting a Handle on Social Bots

By IEEE Spectrum

June 14, 2017

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A new taxonomy of social network botnets seeks to expand on earlier taxonomies.

Indiana University researcher Gregory Maus says his new taxonomy of social networking botnets will be a “broad, flexible framework useful for researchers” seeking both to understand and interact with bots.

Credit: istockphoto

The U.S. Defense Advanced Research Projects Agency two years ago challenged researchers to identify “influence bots,” and the agency now is funding further research on social networks.

As part of that effort, Indiana University researcher Gregory Maus will present one of a growing number of socialbot taxonomies this month at the ACM Web Science (WebSci’17) conference in New York.

Maus says the taxonomy seeks to expand on earlier taxonomies focused on identifying the different types of botnets and categorizing malicious socialbots that flood a Twitter hashtag used to organize political protests.

Maus thinks the new taxonomy will be a more “broad, flexible framework useful for researchers” seeking both to understand and interact with bots.

His research creates categories based on the degree to which a bot tries to pretend to be human, who its owner is, how the bot interacts with other bots, whether it hides its connection to its owner, and its mission.

From IEEE Spectrum
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Abstracts Copyright © 2017 Information Inc., Bethesda, Maryland, USA


 

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from Communications of the ACM: Artificial Intelligence http://ift.tt/2rhUMSy

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