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Trends in academic fields might be able to be detected more easily by studying gross statistics of the communications in the field. The hypertext links of the World Wide Web form an informal citation system similar to the footnote system already in use. Studying the topography of these links and their evolution might provide insights into what any given community thought was important.
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We first solicit diverse opinions on the sensitiveness of private information from crowdsourcing workers, and examine the responses to discover a perceptual model behind the consensuses and disagreements. We then develop a computational scheme using deep neural networks to compute a context-free PrivScore (i.e., the “consensus” privacy score among average users). Finally, we integrate tweet histories, topic preferences and social contexts to generate a personalized context-aware PrivScore....