Visualising context and hierarchy in social media
Suvodeep Mazumdar, Fabio Ciravegna, Anna Lisa Gentile, Vitaveska Lanfranchi · SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University) · 2012
The amount of data available online for analysis and reuse has dramatically increased in the last few years, with the advent of Linked Data and the mass adoption of social media. This has created a new class of users that want and need to consume available datasets to support their information needs but do not possess the technical expertise or the time to use complex querying systems. An example is Emergency Responders (ERs), teams of specialised users that monitor, react and respond to emergencies. Whilst ERs want and need to use these new sources of information, they have very stringent requirements on the type of interface that suits their information needs: the interface needs to be intuitive, highlight important data at a glance, and allow them to understand the context and the specificity of the data. Our contribution to this issue is a new visual analytics approach that focuses on context and specificity of social media content. We extract contextual and hierarchical features from social media messages and use them to provide co-occurring and hierarchical structures to explore large scale, unknown datasets in a highly visual and interactive manner. We introduce a new visualisation paradigm, called Context and Hierarchy chain, that provides means to explore such multidimensional datasets.