Vis enkel innførsel

dc.contributor.authorWani, Mudasir Ahmad
dc.contributor.authorAgarwal, Nancy
dc.contributor.authorBours, Patrick
dc.date.accessioned2022-03-01T12:26:58Z
dc.date.available2022-03-01T12:26:58Z
dc.date.created2022-01-19T13:40:05Z
dc.date.issued2021
dc.identifier.citationProcedia Computer Science. 2021, 189 116-127.en_US
dc.identifier.issn1877-0509
dc.identifier.urihttps://hdl.handle.net/11250/2982092
dc.description.abstractThis study designs an online sexual predator detection system using Social Behavior Biometric (SSB) features. Social biometric focuses on extracting the pattern a user exhibits while interacting and communicating through social networks. The paper addresses the online sexual predator problem by mining the vocabulary and emotional behavior, which could assist in identifying if the user is a benign or predator. The feature-set consists of vocabulary terms that appear differently in predator and victim content. In order to strengthen the detection model, the paper also focuses on distinguishing the two classes of users based on emotions reflected in their conversation. The experiments are performed on the PAN 2012 corpus. Two datasets are created with respect to vocabulary-based and emotion-based features. The results obtained on the test set have proved that by integrating the vocabulary and emotion-based attributes, the performance of the system is significantly enhanced. While comparing, the proposed approach has outperformed top existing methods by obtaining F1, F2, and F0.5 values of 0.95, 0.94, and 0.96 respectively. Furthermore, we also recorded the best accuracy compared to state-of-the-art studies for our proposed SBB-based approach with 99.86%, 99.51%, and 99.88% for Decision Tree (DT), Support Vector Machine (SVM), and Random Forest (RF) respectively.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleSexual-predator Detection System based on Social Behavior Biometric (SSB) Featuresen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber116-127en_US
dc.source.volume189en_US
dc.source.journalProcedia Computer Scienceen_US
dc.identifier.doihttps://doi.org/10.1016/j.procs.2021.05.075
dc.identifier.cristin1984832
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel

Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Med mindre annet er angitt, så er denne innførselen lisensiert som Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal