Israeli Researchers Develop New Method for Detecting Fake Accounts on Social Media Platforms
Many if not most of the world’s most prominent social media
platforms are riddled with countless numbers of fake accounts and bots, which
impact not only upon the quality of use and reliability of information for
users, but also the financials and trustworthiness of the platform and larger
company. With ‘fake news’ being the buzzword of the moment and allegations of political
interference running rife, there has never been a more pressing need to mitigate
this ongoing issue.
Recognising the need for substantial action, a team of
researchers from Israel’s Ben-Gurion University of the Negev and University of
Washington, Seattle recently came together to develop a brand new method for
detecting fake accounts on social networks such as Facebook and Twitter. Dima
Kagan of the Department of Software and Information Systems Engineering at
Ben-Gurion University, who served as lead researcher on the study, stated in no
uncertain terms that “rooting out fake users has never been of greater importance.”
The new method, published in the latest issue of Social
Network Analysis and Mining, works based on a simple assumption; that fake
accounts tend to establish “improbable links” to other users in the networks. Building
from this foundation the process then comprises two main ‘iterations’ (defined
as a set of repeating processes, utterance or commands) which each derive their
basis from machine-learning algorithms.
The first iteration is used to build a “link prediction
classifier”, which subsequently provides an accurate estimation as to whether
or not two particular users were legitimately linked. The second then uses this
data to create new meta-features which researchers then incorporate into a
generic classifier which serves to detect fake profiles.
As it stands there are reportedly more than 200 million fake
accounts on Facebook alone, with Twitter harbouring an estimated 48 million on
their own platform. In Twitter’s case this constitutes around 15% of their active
user base. With this in mind users, investors and advertisers alike will be
hoping this study bears some meaningful fruit and can make some form of impact.
The researchers tested the algorithm on 10 different social networks and it
apparently “performed well” on both simulated and real-world situations,
outperforming other similar tools and showing the potential to enhance cyber
security applications, so prospects sounds good at present.
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Israeli Researchers Develop New Method for Detecting Fake Accounts on Social Media Platforms
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Thursday, April 26, 2018
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Reviewed by Unknown
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Thursday, April 26, 2018
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