Twitris 2.0, a Semantic Web application that facilitates understanding of social perceptions by Semantics-based processing of massive amounts of event-centric data. Twitris 2.0 addresses challenges in large scale processing of social data, preserving spatio-temporal-thematic properties. Twitris 2.0 also covers context based semantic integration of multiple Web resources and expose semantically enriched social data to the public domain. Semantic Web technologies enable the system’s integration and analysis abilities.

Why Twitris?

        Emergence of microblogging platforms such as Twitter, friendfeed etc. have revolutionized how unfiltered, real-time information is disseminated and consumed by citizens. Twitter, has therefore emerged as the preeminent medium for sharing citizen-sensor observations, as was demonstrated in a variety of situations ranging from Mumbai terrorist attack to Iran elections.

While the decentralized information diffusion model offered by twitter has gained momentum and has created avenues for experiential data sharing, millions of observations, shared through tweets, create significant information overload. In many cases it becomes nearly impossible to make sense of the information around a topic of interest. This problem is further compounded by the fact that tweets increasingly integrate other social networking sites (flickr, twitpics) and general Web content(news, Wikipedia, blogs) through embedded links and metadata. Given this data deluge, analyzing the numerous social signals carried by tweets and associated content to find out what is being said about an event (theme), where (spatial), when (temporal), how are key concerns (topics of discussion) changing over a period of time and whether there are regional differences in the opinions on a given topic, can be extremely challenging.