Twitter streams are numerous and very diverse in topics, sentiments and viewpoints.
RENDER is developing a tool called TwiDiViz to structure the inherent knowledge of a very large number of Twitter streams and make it easily accessible and browsable for end-users in an elaborated interface.
Questions, Ideas and Resources
We want YOUR ideas, questions and collaboration for building knowledge-diversity-enabling extensions to Twitter! Below you find resources for getting involved as a developer and a forum to discuss your ideas, questions and remarks.
Mind the possibilities
When you are having ideas how to improve Twitter, keep in mind the possibilities of the technology developed in RENDER for opinion mining, fact coverage, representation and more. To get an overview, check out the deliverables section.
TwiDiViz is a web-based application that enable the analysis and visualization of diversity in Twitter data. This tool uses core RENDER technologies (such as the Knowledge Diversity Ontology (KDO) ontology and the Enrycher service) to process Twitter datasets for the purpose of analyzing the impact of products on basis of sentiment and topic mining.
Using TwiDiViz, users can explore and get familiar with diversity aspects of the Twitter data in two different ways. We offer a static printable report summarizing the results of our diversity-oriented analysis. In addition, we provide an interactive visualizer based on Microsoft Pivot Viewer.
Find the demo at http://twitter.render-project.eu/demo.html.