context-free data analysis with transcendental information cascades
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Context-free data analysis with Transcendental Information Cascades. Markus Luczak-Roesch �University of Southampton, Web and Internet Science @mluczak | http://markus-luczak.de
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[1] Markus Luczak-Roesch, Ramine Tinati, and Nigel Shadbolt. 2015. When Resources Collide: Towards a Theory of Coincidence in Information Spaces. In WWW’15 Companion.
[2] Markus Luczak-Roesch, Ramine Tinati, Max Van Kleek, and Nigel Shadbolt. 2015. From Coincidence to Purposeful Flow? Properties of Transcendental Information Cascades. In IEEE/ACM
International Conference on Advances in Social Networks Analysis and Mining 2015.
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[3] Kleinberg, Jon. "Bursty and hierarchical structure in streams." Data Mining and Knowledge Discovery 7.4 (2003): 373-397.
[4] Subašić, I., & Berendt, B. (2013). Story graphs: Tracking document set evolution using dynamic graphs. Intelligent Data Analysis, 17(1),
125-147.
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Content streams as automata [3]
“The key notion of TTM is burstiness – sudden increases in frequency of text fragments, and all TTM methods aim to model burstiness.” [4]
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