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Informative Value of Individual and Relational Data Compared Through Business-Oriented Community Detection

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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

Despites the great interest caused by social networks in Business Science, their analysis is rarely performed in both a global and systematic way in this field. This could be explained by the fact their practical extraction is a difficult and costly task. One may ask if equivalent information could be retrieved from less expensive, individual data (i.e. describing single individuals instead of pairs). In this work, we try to address this question through group detection. We gather both types of data from a population of students, estimate groups separately using individual and relational data, and obtain sets of clusters and communities, respectively. We measure the overlap between clusters and communities, which turns out to be relatively weak. We also define a predictive model, allowing us to identify the most discriminant attributes for the communities, and to reveal the presence of a tenuous link between the relational and individual data. Our results indicate both types of data convey considerably different information in this specific context, and can therefore be considered as complementary. To emphasize the interest of communities for Business Science, we also conduct an analysis based on hobbies and purchased brands.

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Acknowledgements

We would like to thank Günce Orman, who helped organizing and translating the survey, Siegfried Devoldère who also translated parts of the questions, and Taleb Mohamed El Wely who programmed the electronic form and designed the survey website. Our gratitude also goes to the reviewers, who provided us constructive comments and allowed us to improve the quality of this chapter.

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Authors and Affiliations

  1. Computer Science Department, Galatasaray University, Çırağan Cad. No:36, 34357, Ortaköy/Istanbul, Turkey

    Vincent Labatut

  2. Business Science and Marketing Department, Galatasaray University, Çırağan Cad. No:36, 34357, Ortaköy/Istanbul, Turkey

    Jean-Michel Balasque

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  1. Vincent Labatut
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  2. Jean-Michel Balasque
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Correspondence to Vincent Labatut .

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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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Labatut, V., Balasque, JM. (2013). Informative Value of Individual and Relational Data Compared Through Business-Oriented Community Detection. 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_13

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  • DOI: https://doi.org/10.1007/978-3-7091-1346-2_13

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