NusEye: Visualizing Network Structure to Support Navigation of Aggregated Content

@inproceedings{citeulike:1202774, abstract = {The application of social network analysis techniques, along with graph visualization and interaction, for navigating syndicated web content, a.k.a webfeeds, is presented. Within a webfeed aggregator, a judicious choice of networks and network information can highlight relationships between individual content items and content sources. A key contribution is to apply network analysis to content item and content source relationships in addition to analysis of traditional human networks. Presenting these relationships can improve scannability and prevent source stagnation in content aggregators. This aids in reducing information overload and improving information quality. Three social networks are exploited to generate interactive graphs in particularly useful visual styles. The results of a small initial user study are also presented indicating initial promise for our approach.}, author = {Dennis, B. M. and Jarrett, A. C. }, citeulike-article-id = {1202774}, journal = {System Sciences, 2005. HICSS '05. Proceedings of the 38th Annual Hawaii International Conference on}, keywords = {digital\_library, scholarly\_communication}, pages = {107c}, posted-at = {2007-04-02 13:13:40}, priority = {2}, title = {NusEye: Visualizing Network Structure to Support Navigation of Aggregated Content}, url = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=1385454}, year = {2005} }

TY - CONF ID - citeulike:1202774 L3 - citeulike-article-id:1202774 TI - NusEye: Visualizing Network Structure to Support Navigation of Aggregated Content JF - System Sciences, 2005. HICSS '05. Proceedings of the 38th Annual Hawaii International Conference on SP - 107c EP - 107c N2 - The application of social network analysis techniques, along with graph visualization and interaction, for navigating syndicated web content, a.k.a webfeeds, is presented. Within a webfeed aggregator, a judicious choice of networks and network information can highlight relationships between individual content items and content sources. A key contribution is to apply network analysis to content item and content source relationships in addition to analysis of traditional human networks. Presenting these relationships can improve scannability and prevent source stagnation in content aggregators. This aids in reducing information overload and improving information quality. Three social networks are exploited to generate interactive graphs in particularly useful visual styles. The results of a small initial user study are also presented indicating initial promise for our approach. KW - digital_library KW - scholarly_communication AU - Dennis, BM AU - Jarrett, AC PY - 2005/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1385454 ER -