Deep Neural Network-based Relationship Identification Framework to Discriminate Fake Profile Over Social Media

Involvement of social media like personal, business and political propaganda activities, attracts anti-social activities and has also increased. Anti-social elements get a wider platform to spread negativity after hiding their identity behind fake and false profiles. In this paper, an analytical and methodological user identification framework is developed to significantly binds implicit and explicit link relationship over the end-users graphical perspective. Identify malicious user, its communal information and sockpuppet node. Apart from that, this work provides the concept of the deep neural network approach over the graphical and linguistic perspective of end-user to classify as malicious, fake and genuine. This concept also helps identify the tradeoff between the similarity of nodes attributes and the density of connections to classifying identical profile as sockpuppet over social media.