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Recognising user identity in twitter social networks via text mining

conference contribution
posted on 2013-01-01, 00:00 authored by Sara Keretna, A Hossny, Douglas CreightonDouglas Creighton
Social networks have become a convenient and effective means of communication in recent years. Many people use social networks to communicate, lead, and manage activities, and express their opinions in supporting or opposing different causes. This has brought forward the issue of verifying the owners of social accounts, in order to eliminate the effect of any fake accounts on the people. This study aims to authenticate the genuine accounts versus fake account using writeprint, which is the writing style biometric. We first extract a set of features using text mining techniques. Then, training of a supervised machine learning algorithm to build the knowledge base is conducted. The recognition procedure starts by extracting the relevant features and then measuring the similarity of the feature vector with respect to all feature vectors in the knowledge base. Then, the most similar vector is identified as the verified account.



IEEE Systems, Man and Cybernetics. Conference (2013 : Manchester, England)


3079 - 3082




Manchester, England

Place of publication

Piscataway, N.J.

Start date


End date




Publication classification

E1 Full written paper - refereed

Copyright notice

2013, IEEE

Title of proceedings

SMC 2013 : Proceedings of the 2013 IEEE International Conference on Systems, Man and Cybernetics