Entity resolution in online multiple social networks (@Facebook and linkedIn)

Abstract

The social network is a platform where the user can frame societal relations with people, friends, and colleagues who claim same significance, actions, and real-life connections. Social network is web-based services, and it grants individuals to build their personal profile (public/private) and also maintains the list of users with whom to share connections, post, updates, and view. Today, over 2.9 billion individuals across the globe use the Internet and about 42% of these users actively participate in OSNs. Recent statistics list about 226 active OSNs in 2017. Each online social network (OSN) offers a distinct set of innovative services that easily access to information. The main aim of Twitter is at particular instance; its retweet feature enables quick access to news, campaigns, and mess information, while pinboards of pinterest provide facility to reach the work of artists, photographers, and fashion designers to enjoy these services, accordingly and a user book herself/himself on multiple online social networks (OSNs). Research center shows that 91% users registered themselves on both Twitter and Facebook and 52% users on Twitter, LinkedIn, and Instagram. During registration on any OSN, a user creates an identity for herself/himself listing personal information (profile) and connections and sharing. Since varying policy and purpose of the identity creation on each OSN, quality, quantity, and correctness of her identity vary with the online social network. These give dissimilar existence of the same user and it is scattered across Internet; it has no accurate networks directing to one another. These unequal networks detach his/her from any privacy concerns. It emerges if the identities were implicative collated. However, desperate unlinked networks are a concern for various participants. The application of analysis/findings will be helpful in marketing and job recruitment, where the manager wants to check the employee profile on Facebook and LinkedIn. Facebook will give the detail of social activity and LinkedIn gives professional connection and their past experiences. The analysis/discovery can also be used in the security domain, recommendation system human resource management, and advertisement. The paper is organized in six parts: part I contains an introduction to the social network, part II contains literature survey, part III explains the limitation and research gap, part IV contains proposed methodology and block diagram, and part V contains conclusion and references.