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Application of Social Network Metrics to a Trust-Aware Collaborative Model for Generating Personalized User Recommendations

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The Influence of Technology on Social Network Analysis and Mining

Part of the book series: Lecture Notes in Social Networks ((LNSN,volume 6))

Abstract

Social network analysis has emerged as a key technique in modern sociology, but has recently gained a lot of interest in Web mining research, because of the advent and the increasing popularity of social media, such as blogs, social networks, micro-blogging, customer review sites etc. Such media often serve as platforms for information dissemination and product placement or promotion. One way to improve the quality of recommendations provided to the members of social networks is to use trustworthy resources. In this environment, community-based reputation can help estimating the trustworthiness of individual users. Consequently, influence and trust are becoming essential qualities among user interactions. In this work, we perform an extensive study of various metrics related to the aforementioned elements, and of their effect in the process of information propagation in social networks. In order to better understand the properties of links and the dynamics of social networks, we distinguish between permanent and transient links and in the latter case, we consider the link freshness. Moreover, we distinguish between the propagation of trust in a local level and the effect of global influence and compare suggestions provided by locally trusted or globally influential users.

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Notes

  1. 1.

    We assume that the system does not process the complete history of user ratings and friendship links from the very beginning of the community, but only the most recent interactions. Thus we use the term “system memory” to refer to the size (in time units) of this history log.

  2. 2.

    http://www.trustlet.org/wiki

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Author information

Authors and Affiliations

  1. Department of Informatics and Telematics, Harokopio University of Athens, Athens, Greece

    Iraklis Varlamis

  2. Computer Engineering Department, San Jose State University, San Jose, CA, USA

    Magdalini Eirinaki

  3. Department of Informatics and Telecommunications Engineering, University of Western Macedonia, Kozani, Greece

    Malamati Louta

Authors
  1. Iraklis Varlamis
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  2. Magdalini Eirinaki
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  3. Malamati Louta
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Corresponding author

Correspondence to Iraklis Varlamis .

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Editors and Affiliations

  1. Department of Computer Engineering, TOBB University, Sogutozu Cad No. 43, Sogutozu Ankara, Turkey

    Tansel Özyer

  2. Computer Science, University of Calgary, University Dr. NW 2500, Calgary, T2N 1N4, Canada

    Jon Rokne

  3. IPSC, European Commission Joint Research Cent., Via Enrico Fermi 2749, Ispra, 21027, Italy

    Gerhard Wagner

  4. De Wetstraat 16, Leiden, 2332 XT, Netherlands

    Arno H.P. Reuser

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Varlamis, I., Eirinaki, M., Louta, M. (2013). Application of Social Network Metrics to a Trust-Aware Collaborative Model for Generating Personalized User Recommendations. In: Özyer, T., Rokne, J., Wagner, G., Reuser, A. (eds) The Influence of Technology on Social Network Analysis and Mining. Lecture Notes in Social Networks, vol 6. Springer, Vienna. https://doi.org/10.1007/978-3-7091-1346-2_3

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  • DOI: https://doi.org/10.1007/978-3-7091-1346-2_3

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  • Online ISBN: 978-3-7091-1346-2

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