—We introduce a novel set of social network analysis based algorithms for mining the Web, blogs, and online forums to identify trends and find the people launching these new tren...
Peter A. Gloor, Jonas Krauss, Stefan Nann, Kai Fis...
In this paper, we propose a methodology to predict the popularity of online contents. More precisely, rather than trying to infer the popularity of a content itself, we infer the l...
Mining sentiment from user generated content is a very important task in Natural Language Processing. An example of such content is threaded discussions which act as a very import...
By examining the information practices of a punk-rock subculture, we investigate the limits of social media systems, particularly limits exposed by practices of secrecy. Looking a...
Jessica Lingel, Aaron Trammell, Joe Sanchez, Mor N...
In this paper, we undertake a large-scale study of online user behavior based on search and toolbar logs. We propose a new CCS taxonomy of pageviews consisting of Content (news, p...