AIS Electronic Library (AISeL)

Users of Social Networking Sites (SNS) consume SNS content by means of online social streams such as the newsfeed system on Facebook. In this regard, a Facebook newsfeed content may comprise different kinds of user generated content, but also editorial content provided by fan pages, business pages or advertisers. Before being displayed on the Facebook newsfeed, contents are automatically pre-selected based on information filtering algorithms. Information filtering algorithms, in the form of Facebook’s edgerank system, are challenged to address the growing diversity of SNS content, but also the preferences of individual users. Distinct knowledge about the preferences of users for different kinds of SNS content can efficiently improve or complement established information filtering techniques. In this study we investigate factors that determine the attractiveness of SNS content for users. Thereby, we contribute a new facet in the understanding and support of users’ needs with regard to their consumption of SNS content. Our results allow improvement of existing information filtering techniques and to anticipate information flows on SNS (e.g. for the sake of viral marketing). We have developed our results based on a grounded theory study founded on 37 qualitative interviews with Facebook users.

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