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Project

REVEALing hidden concepts in social media (REVEAL)

The world of media and communication is currently experiencing enormous disruptions: from one-way communication and word of mouth exchanges, we have moved to bi- or multidirectional communication patterns. No longer can a selected few (e.g. media organisations and controllers of communication channels) act as gatekeepers, deciding what is communicated to whom and what not. Individuals now have the opportunity to access information directly from primary sources, through a channel we label ‘e-word of mouth’, or what we commonly call 'Social Media'.

A key problem is that it takes a lot of effort to distinguish useful information from the 'noise' (e.g. useless or misleading information). Finding relevant information is often tedious. This challenge has become the focus of various research efforts. Many concentrate on the automatic discovery of information by adapting semantic search and retrieval technologies to the particularities of Social Media content. REVEAL, however, aims to discover higher level concepts hidden within information. In Social Media we do not only have bare content; we also have interconnected sources. We have to deal with interactions between them, and we have many indicators about the context within which content is used, and interactions taking place. A core challenge is to decipher interactions of individuals in permanently changing constellations, and do so in real time. This is what we aim for!

We will reveal much more than bare content. Further to discovering what is being said, we will determine how trustworthy that information is. We will predict contributor impact and how much or to what extent all this affects reputation or influence. This allows us to automatically judge the quality and accuracy of content, and bring us to predicting future trends with greater accuracy.

We label all this Social Media modalities. The core of our work is to reveal hidden modalities for the benefit of a better understanding and utilisation of the Social Media world.

Date:1 Nov 2013 →  31 Dec 2016
Keywords:information extraction, content verification, semantic analysis, social network analysis, social media
Disciplines:Law