Collective dynamics of social annotation
- aComplex Networks Lagrange Laboratory, Institute for Scientific Interchange, 10133 Turin, Italy;
- bCentre de Physique Théorique, Centre National de la Recherche Scientifique, Unité Mixte de Recherche 6207, Campus de Luminy, Case 907, 13288 Marseille Cedex 9, France;
- cDipartimento di Fisica, “Sapienza” Università di Roma, Piazzale Aldo Moro 5, 00185 Rome, Italy; and
- dLaboratoire de Physique Théorique Centre National de la Recherche Scientifique, Unité Mixte de Recherche 8627, Université Paris-Sud, 91405 Orsay Cedex, France
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Edited by H. Eugene Stanley, Boston University, Boston, MA, and approved April 17, 2009 (received for review February 2, 2009)
Abstract
The enormous increase of popularity and use of the worldwide web has led in the recent years to important changes in the ways people communicate. An interesting example of this fact is provided by the now very popular social annotation systems, through which users annotate resources (such as web pages or digital photographs) with keywords known as “tags.” Understanding the rich emergent structures resulting from the uncoordinated actions of users calls for an interdisciplinary effort. In particular concepts borrowed from statistical physics, such as random walks (RWs), and complex networks theory, can effectively contribute to the mathematical modeling of social annotation systems. Here, we show that the process of social annotation can be seen as a collective but uncoordinated exploration of an underlying semantic space, pictured as a graph, through a series of RWs. This modeling framework reproduces several aspects, thus far unexplained, of social annotation, among which are the peculiar growth of the size of the vocabulary used by the community and its complex network structure that represents an externalization of semantic structures grounded in cognition and that are typically hard to access.
Footnotes
- 1To whom correspondence should be addressed. E-mail: vittorio.loreto{at}roma1.infn.it
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Author contributions: C.C., A. Barrat, A. Baldassarri, G.S., and V.L. designed research, performed research, contributed new reagents/analytic tools, analyzed data, and wrote the paper.
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The authors declare no conflict of interest.
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This article is a PNAS Direct Submission.
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This article contains supporting information online at www.pnas.org/cgi/content/full/0901136106/DCSupplemental.
