Finding strong groups of friends in online social networks

Vinh, Eleonora, 2015

Art der Arbeit Master Thesis
Betreuende Dozierende Telesko, Rainer
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Over the past several years, online social media platforms have gained in popularity. Never has it been as easier to connect to others as it is with social media platforms. Users can quickly gain many friends or followers. In some cases, strong friendships are formed. But what if a user wants to purposely search for these potential strong relationships among their friends or followers? A solution based on existing data in online social media platforms can help users to identify these potential strong relationships, but the current functionalities on platforms like Facebook, Google + or Twitter don’t offer a satisfying solution. This research applies a data mining concept and enhances it with key indicators based on the definition of a strong online relationship. The resulting mock-up solution design should support users in finding these potentially strong friends or followers within the large number of friends or followers on their online social media networks.The mock-up solution was presented to private and commercial users so that they could understand how the solution could potentially benefit them. In 15 qualitative interviews with seven private users, seven commercial and one social media platform subject matter expert, the thesis statement has been confirmed. Almost all participants feel they could use the proposed solution to find potentially strong relationships, to target strong followers better or to invite them to a special event. The most remarked upon concerns are data policy and data security, while the most suggested feature is the ability to identify bad relationships with an option to block them.The research concludes with an outlook for further extended studies: an empirical market research on a selected target group or a developed enhanced solution tested in a field study.
Studiengang: Business Information Systems (Master)
Vertraulichkeit: öffentlich
Art der Arbeit
Master Thesis
Autorinnen und Autoren
Vinh, Eleonora
Betreuende Dozierende
Telesko, Rainer
Sprache der Arbeit
Business Information Systems (Master)
Standort Studiengang