Scientific Publications

@inproceedings{Nazemi2014b,

title = {Adaptive Visualization of Social Media Data for Policy Modeling},

author = {Kawa Nazemi and Dirk Burkhardt and Wilhelm Retz and Jörn Kohlhammer},

editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Ryan McMahan and Jason Jerald and Hui Zhang and Steven M. Drucker and Chandra Kambhamettu and Maha El Choubassi and Zhigang Deng and Mark Carlson},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2014isvc-ii.pdf, Paper as PDF},

doi = {10.1007/978-3-319-14249-4_32},

isbn = {978-3-319-14249-4},

year  = {2014},

date = {2014-12-08},

booktitle = {Advances in Visual Computing. ISVC 2014},

volume = {8887},

pages = {333--344},

publisher = {Springer International Publishing},

address = {Switzerland},

series = {Lecture Notes in Computer Science, vol 8887},

abstract = {The visual analysis of social media data emerged a huge number of interactive visual representations that use different characteristics of the data to enable the process of information acquisition. The social data are used in the domain of policy modeling to gather information about citizens' demands, opinions, and requirements and help to decide about political policies. Although existing systems already provide a huge number of visual analysis tools, the search and exploration paradigm is not really clear. Furthermore, the systems commonly do not provide any kind of human centered adaptation for the different stakeholders involved in the policy making process. In this paper, we introduce a novel approach that investigates the exploration and search paradigm from two different perspectives and enables a visual adaptation to support the exploration and analysis process.},

keywords = {Information Visualization, Policy Modeling, Search Paradigm, Social Media Data, Visual Variable},

pubstate = {published},

tppubtype = {inproceedings}

}