Uncovering trolls and malicious or spammy accounts on social media is increasingly difficult as the miscreants find more and more ways to camouflage themselves as seemingly legitimate. Writing in the International Journal of Intelligent Engineering Informatics, researchers in India have developed an algorithm based on ant-colony optimization that can effectively detect accounts that represent a threat to normal users.

Asha Kumari and Balkishan Department of Computer Science and Applications at Maharshi Dayanand University, in Rohtak, India, explain that the connections between twitter users are analogous to the pheromone chemical communication between ants and this can be modeled in an algorithm based on how ant colonies behave to reveal the strongest connections in the twitter network and so uncover the accounts that one might deem as threatening to legitimate users.

The team's tests on their system were successful in terms of precision, recall, f-measure, true-positive rate, and false-positive rate based on 26 features examined by the system played against almost 41,500 user accounts attracted to honeypots. Moreover, they report that the approach is superior to existing techniques. The team adds that they hope to be able to improve the system still further by adding so-called machine learning into the algorithm so that it can be trained to better identify threatening accounts based on data from known threats and legitimate accounts.

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More information: Asha Kumari et al. Detection of threatening user accounts on Twitter social media database, International Journal of Intelligent Engineering Informatics (2019). DOI: 10.1504/IJIEI.2019.103626