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      Social Features of Online Networks: The Strength of Intermediary Ties in Online Social Media

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          An increasing fraction of today's social interactions occur using online social media as communication channels. Recent worldwide events, such as social movements in Spain or revolts in the Middle East, highlight their capacity to boost people's coordination. Online networks display in general a rich internal structure where users can choose among different types and intensity of interactions. Despite this, there are still open questions regarding the social value of online interactions. For example, the existence of users with millions of online friends sheds doubts on the relevance of these relations. In this work, we focus on Twitter, one of the most popular online social networks, and find that the network formed by the basic type of connections is organized in groups. The activity of the users conforms to the landscape determined by such groups. Furthermore, Twitter's distinction between different types of interactions allows us to establish a parallelism between online and offline social networks: personal interactions are more likely to occur on internal links to the groups (the weakness of strong ties); events transmitting new information go preferentially through links connecting different groups (the strength of weak ties) or even more through links connecting to users belonging to several groups that act as brokers (the strength of intermediary ties).

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          Most cited references 33

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          The spread of behavior in an online social network experiment.

           Damon Centola (2010)
          How do social networks affect the spread of behavior? A popular hypothesis states that networks with many clustered ties and a high degree of separation will be less effective for behavioral diffusion than networks in which locally redundant ties are rewired to provide shortcuts across the social space. A competing hypothesis argues that when behaviors require social reinforcement, a network with more clustering may be more advantageous, even if the network as a whole has a larger diameter. I investigated the effects of network structure on diffusion by studying the spread of health behavior through artificially structured online communities. Individual adoption was much more likely when participants received social reinforcement from multiple neighbors in the social network. The behavior spread farther and faster across clustered-lattice networks than across corresponding random networks.
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            Is Open Access

            Maps of random walks on complex networks reveal community structure

            To comprehend the multipartite organization of large-scale biological and social systems, we introduce a new information theoretic approach that reveals community structure in weighted and directed networks. The method decomposes a network into modules by optimally compressing a description of information flows on the network. The result is a map that both simplifies and highlights the regularities in the structure and their relationships. We illustrate the method by making a map of scientific communication as captured in the citation patterns of more than 6000 journals. We discover a multicentric organization with fields that vary dramatically in size and degree of integration into the network of science. Along the backbone of the network -- including physics, chemistry, molecular biology, and medicine -- information flows bidirectionally, but the map reveals a directional pattern of citation from the applied fields to the basic sciences.
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              Neocortex size as a constraint on group size in primates

               R.I.M. Dunbar (1992)

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                11 January 2012
                : 7
                : 1
                [1 ]Instituto de Fisica Interdisciplinaria y Sistemas Complejos (CSIC-UIB), Palma de Mallorca, Spain
                [2 ]Instituto de Ingeniera del Conocimiento, Universidad Autónoma de Madrid, Madrid, Spain
                [3 ]Instituto de Ciencias Matemáticas CSIC-UAM-UC3M-UCM, Departamento de Matemáticas y GISC, Universidad Carlos III de Madrid, Leganés, Spain
                [4 ]Telefónica Research, Barcelona, Spain
                [5 ]3scale Networks, Barcelona, Spain
                University of Zaragoza, Spain
                Author notes

                Conceived and designed the experiments: PAG JJR EM. Performed the experiments: PAG JJR EM JMP VME. Analyzed the data: PAG JJR EM JMP VME. Contributed reagents/materials/analysis tools: PAG JJR. Wrote the paper: PAG JJR EM JMP VME.

                Grabowicz et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 9
                Research Article
                Management Engineering
                Management Planning and Control
                Applied Mathematics
                Interdisciplinary Physics
                Social and Behavioral Sciences



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