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219 sites; many of these sites allow users to host content, which in turn can be linked to other users and content. Establishing the structure and dynamics of the content graph is an open problem, the solution to which will enable us to understand how content is introduced in these systems, how data gains popularity, how users interact with popular versus personal data, and whether these trends can be hardened to prevent deliberate manipulation. Similarly, the data we collected on the growth of online social networks can be used to test previously proposed growth models to see how well they match the observations, as well as to guide the development of new models based on empirical data. Users often share very personal information on today’s online social networks, with little regard for who will be allowed to view the content. Anecdotal evidence suggests that this often results in unintended consequences, ranging from public em- barrassment to job loss. The underlying problem is, essentially, ensuring privacy for users while allowing them to share information and knowledge freely. This problem has aspects that span the areas of security, systems, and interface design. Thus, one challenge is to design mechanisms that enable the wide-spread sharing that users de- sire while ensuring that users understand who else is able to access their content. One potential first step to solving this problem is to use communities as an abstraction for expressing privacy policies, allowing users to share content with more than just their friends but not necessarily with the entire world. Another problem concerns ensuring the relevance of information obtained. In priorPDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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