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Analyzing the Dynamics of Communication in Online Social Networks

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Handbook of Social Network Technologies and Applications

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Abstract

This chapter deals with the analysis of interpersonal communication dynamics in online social networks and social media. Communication is central to the evolution of social systems. Today, the different online social sites feature variegated interactional affordances, ranging from blogging, micro-blogging, sharing media elements (i.e., image, video) as well as a rich set of social actions such as tagging, voting, commenting and so on. Consequently, these communication tools have begun to redefine the ways in which we exchange information or concepts, and how the media channels impact our online interactional behavior. Our central hypothesis is that such communication dynamics between individuals manifest themselves via two key aspects: the information or concept that is the content of communication, and the channel i.e., the media via which communication takes place. We present computational models and discuss large-scale quantitative observational studies for both these organizing ideas. First, we develop a computational framework to determine the “interestingness” property of conversations cented around rich media. Second, we present user models of diffusion of social actions and study the impact of homophily on the diffusion process. The outcome of this research is twofold. First, extensive empirical studies on datasets from YouTube have indicated that on rich media sites, the conversations that are deemed “interesting” appear to have consequential impact on the properties of the social network they are associated with: in terms of degree of participation of the individuals in future conversations, thematic diffusion as well as emergent cohesiveness in activity among the concerned participants in the network. Second, observational and computational studies on large social media datasets such as Twitter have indicated that diffusion of social actions in a network can be indicative of future information cascades. Besides, given a topic, these cascades are often a function of attribute homophily existent among the participants. We believe that this chapter can make significant contribution into a better understanding of how we communicate online and how it is redefining our collective sociological behavior.

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Notes

  1. 1.

    Also referred to in popular culture as a “meme.”

  2. 2.

    To recall, X(i, : ) is the ith row of the 2-dimensional matrix X.

  3. 3.

    Henceforth referred to as the baseline social graph G.

  4. 4.

    For simplicity, we omit specifying the attribute value υ in the rest of the section, and refer to G(ak = υ) as the “attribute social graph” G(ak).

  5. 5.

    Since we discuss our problem formulation and methodology for a specific social action, the dependence of different concepts on Or is omitted in the rest of the section for simplicity.

  6. 6.

    Note, a diffusion series is similar to a diffusion tree as in [4, 23], however we call it a “series” since it is constructed progressively over a period of time and allows a node to have multiple sources of diffusion.

  7. 7.

    Without loss of generalization, we omit the topic θ in the variables in this subsection for the sake of simplicity.

  8. 8.

    http://www.google.com/intl/en/trends/about.html

  9. 9.

    http://news.google.com/

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Authors and Affiliations

  1. Arizona State University, Tempe, AZ, USA

    Munmun De Choudhury

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  1. Munmun De Choudhury
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  2. Hari Sundaram
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  3. Ajita John
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  4. Doree Duncan Seligmann
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Correspondence to Munmun De Choudhury .

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Editors and Affiliations

  1. Dept. of Comp. & Elect. Engin. and, Florida Atlantic University, Glades Road 777, Boca Raton, 33431, Florida, USA

    Borko Furht

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De Choudhury, M., Sundaram, H., John, A., Seligmann, D.D. (2010). Analyzing the Dynamics of Communication in Online Social Networks. In: Furht, B. (eds) Handbook of Social Network Technologies and Applications. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7142-5_4

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  • DOI: https://doi.org/10.1007/978-1-4419-7142-5_4

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