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Abstract
Twitter represents a large complex network of users with diverse and continuously evolving interests. Discussions and interactions range from very small to very large groups of people and most of them occur in the public. Interests are both long and short term and are expressed by the content generated by the users as well as via the Twitter follow graph, i.e. who is following whose content.
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Twitter, USA
Aleksander Kołcz
- Aleksander Kołcz
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Editors and Affiliations
Institute AIFB, Karlsruhe Institute of Technology, Englerstrasse 11, 76131, Karlsruhe, Germany
Elena Simperl
CITEC, University of Bielefeld, Morgenbreede 39, 33615, Bielefeld, Germany
Philipp Cimiano
Siemens AG Österreich, Siemensstrasse 90, 1210, Vienna, Austria
Axel Polleres
Technical University of Madrid, C/ Severo Ochoa, 13, 28660, Boadilla del Monte, Madrid, Spain
Oscar Corcho
STLab, ISTC-CNR, Via Nomentana 56, 00161, Rome, Italy
Valentina Presutti
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© 2012 Springer-Verlag Berlin Heidelberg
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Kołcz, A. (2012). Large Scale Learning at Twitter. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds) The Semantic Web: Research and Applications. ESWC 2012. Lecture Notes in Computer Science, vol 7295. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30284-8_4
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