Scientists are always working to determine which articles are interesting to them, timely, and relevant to their research. If working in an unfamiliar research area, searching for papers becomes even more difficult. By allowing users to vote on the prominence of links, social news sites like Slashdot, Digg, and reddit.com have addressed the issue of surfacing new and interesting content from across the internet. Moreover, they provide opportunities to provide context and comment on the content.
In the era of big data and personalization, websites and (mobile) applications collect an increasingly large amount of personal information about their users. The large majority of users decide to disclose some but not all information that is requested from them. They trade off the anticipated benefits with the privacy risks of disclosure, a decision process that has been dubbed privacy calculus. Such decisions are inherently difficult though, because they may have uncertain repercussions later on that are difficult to weigh against the (possibly immediate) gratification of disclosure. How can we help users to balance the benefits and risks of information disclosure in a user-friendly manner, so that they can make good privacy decisions?