TY - CPAPER SN - 978-0-7695-5670-3 AU - Scharl, Arno AU - Weichselbraun, Albert AU - Göbel, Max AU - Rafelsberger, Walter AU - Kamolov, Ruslan T1 - Scalable Knowledge Extraction and Visualization for Web Intelligence T2 - Proceedings of the 49th Annual Hawaii International Conference on System Sciences ED - Bui, Tung X. ED - Sprague, Ralph H. PY - 2016 CY - Piscataway, NJ PB - Institute of Electrical and Electronic Engineers (IEEE) UR - https://doi.org/10.1109/HICSS.2016.467 SP - 3749 EP - 3757 AB - Understanding stakeholder perceptions and assessing the impact of campaigns are key questions of communication experts. Web intelligence platforms help to answer such questions, provided that they are scalable enough to analyze and visualize information flows from volatile online sources in real time. This paper presents a distributed architecture for aggregating Web content repositories from Web sites and social media streams, memory-efficient methods to extract factual and affective knowledge, and interactive visualization techniques to explore the extracted knowledge. The presented examples stem from the Media Watch on Climate Change, a public Web portal that aggregates environmental content from a range of online sources. Y3 - 21.05.2021 C7 - 49th Hawaii International Conference on System Sciences (HICSS) C1 - Koloa, HI, 5.-8. Januar M4 - Citavi ER -