nach oben

Social Network Analysis and Mining

Erschienen in:

01.12.2017 | Original Article

Over-time measurement of triadic closure in coauthorship networks

verfasst von: Jinseok Kim, Jana Diesner

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Applying the concept of triadic closure to coauthorship networks means that scholars are likely to publish a joint paper if they have previously coauthored with the same people. Prior research has identified moderate to high (20 to 40%) closure rates; suggesting this mechanism is a reasonable explanation for tie formation between future coauthors. We show how calculating triadic closure based on prior operationalizations of closure, namely Newman’s measure for one-mode networks (NCC) and Opsahl’s measure for two-mode networks (OCC) may lead to higher amounts of closure compared to measuring closure over time via a metric that we introduce and test in this paper. Based on empirical experiments using four large-scale, longitudinal datasets, we find a lower bound of 1–3% closure rates and an upper bound of 4–7%. These results motivate research on new explanatory factors for the formation of coauthorship links.

Vorheriger Artikel Vulnerability of clustering under node failure in complex networks

Nächster Artikel The mechanism of collapse of the Friendster network: What can we learn from the core structure of Friendster?

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Transitivity seems to be associated more commonly with directed networks (Wasserman and Faust 1994) than with undirected ones. Many network research papers and software packages implementing the Newman metric (2001b) still use transitivity to refer to triadic closure.

The triadic closure contains three cases of 2-path closure: (1) Y–X–Z closed by Y–Z, (2) X–Z–Y closed by Y–X, and (3) Z–Y–X closed by X–Z. This also applies to Case 2 in Table 2.

The triadic closure contains three cases of 4-path closure: (1) Y–A–X–B–Z closed by Y–C–Z, (2) X–B–Z–C–Y closed by Y–A–X, and (3) Z–C–Y–A–X closed by X–B–Z.

Although calculated against the same dataset, the clustering coefficient by the Newman (2001b) method in Opsahl (2013) is 0.3596, while the one in Newman (2001b) is 0.348.

Opsahl (2013) never uses the clustering coefficient defined for two-mode networks as an indicator of the probability of two scientists collaborating when they have a third coauthor in common.

http://dblp.uni-trier.de/xml/.

The list of 392 journals was obtained from Thomson Reuters Journal Citation Report 2012 for the Computer Science category. Then, those journals’ names and papers published in these journals were searched for in DBLP.

http://journals.aps.org/datasets.

https://www.nlm.nih.gov/bsd/licensee/medpmmenu.html.

http://scholar.ndsl.kr/index.do.

The 4-path in Case 1 is Y–A–X–B–Z. The 4-paths in Case 2 are: (1) Y–A–X–B–Z, (2) Y–A–W–B–Z, and (3) Y–C–X–B–Z.

In 2010, OCC (0.34) surpasses NCC (0.33).

4-paths by OCC: (1) Y–B–X–C–Z (closed by Z–D–Y), (2) Y–A–X–C–Z (closed by Z–D–Y), (3) X–C–Z–D–Y (closed by Y–A–X or Y–B–X), (4) Z–D–Y–A–X (closed by X–C–Z), (5) Z–D–Y–B–X (closed by X–C–Z), (6) X–C–Z–E–W, and (7) W–E–Z–D–Y.

2-paths by NCC: (1) Y–X–Z (Y–Z), (2) X–Z–Y (Y–Z), (3) Z–Y–X (X–Z), (4) W–Z–X, and (5) W–Z–Y.

4-paths by TCC: (1) Y–A and B–X–C–Z (closed by Z–D–Y) and (2) X–C–Z–E–W.

Barabási AL, Jeong H, Neda Z, Ravasz E, Schubert A, Vicsek T (2002) Evolution of the social network of scientific collaborations. Phys A Stat Mech Appl 311(3–4):590–614. doi:10.1016/s0378-4371(02)00736-7 MathSciNetCrossRefMATH

Burt RS (2005) Brokerage and closure: an introduction to social capital. Oxford University Press, Oxford

Çavuşoğlu A, Türker İ (2013) Scientific collaboration network of Turkey. Chaos, Solitons Fractals 57:9–18CrossRef

Csardi G, Nepusz T (2006) The igraph software package for complex network research. Inter J Complex Syst 1695. http://igraph.org

Fegley BD, Torvik VI (2013) Has large-scale named-entity network analysis been resting on a flawed assumption? PLoS ONE 8(7):1–16. doi:10.1371/journal.pone.0070299 CrossRef

Franceschet M (2011) Collaboration in computer science: a network science approach. J Am Soc Inf Sci Technol 62(10):1992–2012. doi:10.1002/asi.21614 CrossRef

Grossman JW (2002) Patterns of collaboration in mathematical research. SIAM News 35(9):8–9

Hâncean M-G, Perc M (2016) Homophily in coauthorship networks of East European sociologists. Sci Rep. doi:10.1038/srep36152

Hâncean M-G, Perc M, Vlăsceanu L (2014) Fragmented romanian sociology: growth and structure of the collaboration network. PLoS ONE 9(11):e113271CrossRef

Holland PW, Leinhardt S (1970) Method for detecting structure in sociometric data. Am J Sociol 76(3):492. doi:10.1086/224954 CrossRef

Kim J, Diesner J (2015) The effect of data pre-processing on understanding the evolution of collaboration networks. J Informetr 9(1):226–236. doi:10.1016/j.joi.2015.01.002 CrossRef

Kim J, Diesner J (2016) Distortive effects of initial-based name disambiguation on measurements of large-scale coauthorship networks. J Assoc Inf Sci Technol 67(6):1446–1461. doi:10.1002/asi.23489 CrossRef

Kim J, Tao L, Lee S-H, Diesner J (2016) Evolution and structure of scientific co-publishing network in Korea between 1948–2011. Scientometrics 107(1):27–41. doi:10.1007/s11192-016-1878-5 CrossRef

Kossinets G, Watts DJ (2006) Empirical analysis of an evolving social network. Science 311(5757):88–90. doi:10.1126/science.1116869 MathSciNetCrossRefMATH

Liben-Nowell D, Kleinberg J (2007) The link-prediction problem for social networks. J Am Soc Inform Sci Technol 58(7):1019–1031. doi:10.1002/asi.20591 CrossRef

Lind PG, Gonzalez MC, Herrmann HJ (2005) Cycles and clustering in bipartite networks. Phys Rev E 72(5):056127. doi:10.1103/PhysRevE.72.056127 CrossRef

Martin T, Ball B, Karrer B, Newman MEJ (2013) Coauthorship and citation patterns in the Physical Review. Phys Rev E 88(1):012814-1–012814-9. doi:10.1103/PhysRevE.88.012814 CrossRef

McPherson M, Smith-Lovin L, Cook JM (2001) Birds of a feather: homophily in social networks. Ann Rev Sociol 27:415–444. doi:10.1146/annurev.soc.27.1.415 CrossRef

Moody J (2004) The structure of a social science collaboration network: disciplinary cohesion from 1963 to 1999. Am Sociol Rev 69(2):213–238CrossRef

Newman MEJ (2001a) Clustering and preferential attachment in growing networks. Phys Rev E. doi:10.1103/PhysRevE.64.025102

Newman MEJ (2001b) The structure of scientific collaboration networks. Proc Natl Acad Sci USA 98(2):404–409. doi:10.1073/pnas.021544898 MathSciNetCrossRefMATH

Newman MEJ, Strogatz SH, Watts DJ (2001) Random graphs with arbitrary degree distributions and their applications. Phys Rev E 64(2):026118CrossRef

Opsahl T (2009) Structure and evolution of weighted networks. University of London (Queen Mary College), London

Opsahl T (2013) Triadic closure in two-mode networks: redefining the global and local clustering coefficients. Soc Netw 35(2):159–167CrossRef

Perc M (2010) Growth and structure of Slovenia’s scientific collaboration network. J Informetr 4(4):475–482CrossRef

Rapoport A (1953) Spread of information through a population with socio-structural bias: I. Assumption of transitivity. Bull Math Biophys 15(4):523–533MathSciNetCrossRef

Reitz F, Hoffmann O (2011) Did they notice? A case-study on the community contribution to data quality in DBLP. In: Gradmann S, Borri F, Meghini C, Schuldt H (eds) Research and advanced technology for digital libraries, TPDL 2011, vol 6966. Springer, Berlin, pp 204–215CrossRef

Robins G, Alexander M (2004) Small worlds among interlocking directors: network structure and distance in bipartite graphs. Comput Math Organ Theory 10(1):69–94. doi:10.1023/B:CMOT.0000032580.12184.c0 CrossRefMATH

Torvik VI, Smalheiser NR (2009) Author name disambiguation in MEDLINE. ACM Trans Knowl Discov Data 3(3):1–29. doi:10.1145/1552303.1552304 CrossRef

Türker İ, Çavuşoğlu A (2016) Detailing the co-authorship networks in degree coupling, edge weight and academic age perspective. Chaos, Solitons Fractals 91:386–392CrossRef

Türker İ, Durgut R, Çavuşoğlu A (2016) Co-authorship network comparison of four Turkish universities. In: Paper presented at the international conference on research in education & science, Bodrum, Turkey

Wasserman S, Faust K (1994) Social network analysis: methods and applications. Cambridge University Press, New YorkCrossRefMATH

Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’networks. Nature 393(6684):440–442CrossRefMATH

Titel: Over-time measurement of triadic closure in coauthorship networks
verfasst von: Jinseok Kim
Jana Diesner
Publikationsdatum: 01.12.2017
Verlag: Springer Vienna
Erschienen in: Social Network Analysis and Mining / Ausgabe 1/2017
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-017-0428-3

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 1/2017

HellRank: a Hellinger-based centrality measure for bipartite social networks

Introduction to the topical issue on semantic social networks and media applications

Vulnerability of clustering under node failure in complex networks

Activity correlation spectroscopy: a novel method for inferring social relationships from activity data

Incremental maintenance of all-pairs shortest paths in relational DBMSs

Data warehouse design approaches from social media: review and comparison

Premium Partner