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Abstract
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| Over the past years, new technologies and specially online social networks have penetrated into the world?s population at an accelerated pace. An important feature of these communication tools is that they provide a large amount of user generated content, which is certainly attracting scientific research. In our study we use the data available from Twitter, to unveil and analyze the structural and dynamical patterns from the user interactions, in order to characterize the emergent collective behavior. We have focused our studies around relevant events such as political protests, electoral processes and the propagation of breaking news, which present several critical phenomena features, such as bursty growth and power law distributions. We use the complex network theory to represent the phenomena and found community structures, compound by users with highly heterogeneous profiles. Such profiles do not have the same impact in the event development, and therefore we have being able to classify them according to their role in the information diffusion process. | |
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International
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Si |
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Congress
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European Conference on Complex Systems (ECCS'12) [http://eccs2012.eu/] |
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960 |
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Place
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Bruselas (Bélgica) |
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Reviewers
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Si |
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ISBN/ISSN
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00-000-000-000-00 |
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Start Date
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03/09/2012 |
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End Date
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07/09/2012 |
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From page
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96 |
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To page
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96 |
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ECCS '12 Brussels. Book of Abstracts [http://eccs2012.eu/media/eccs2012_book_of_abstracts.pdf] |