IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v3y1974i2p123-171.html
   My bibliography  Save this article

A Review of Mathematical Methods in Sociometry

Author

Listed:
  • Richard C. Roistacher

    (Center for Advanced Computation, University of Illinois at Urbana)

Abstract

Current mathematical and computer methods for the analysis of group and organizational structures of communication and evaluation are reviewed. Sociometric data collection, the detection of cliques and subgroups, sociometric index construction, and computer methods in sociometry are discussed. Clique detection methods are classified as either linkage methods, in which sociometric data are treated as a linear graph, or as distance methods, in which data are treated as a configuration of points in a space. Several linkage and distance analysis methods are discussed and compared. It is suggested that some of the methods of numerical taxonomy could be applied to the analysis of group and organizational structures.

Suggested Citation

  • Richard C. Roistacher, 1974. "A Review of Mathematical Methods in Sociometry," Sociological Methods & Research, , vol. 3(2), pages 123-171, November.
  • Handle: RePEc:sae:somere:v:3:y:1974:i:2:p:123-171
    DOI: 10.1177/004912417400300201
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/004912417400300201
    Download Restriction: no

    File URL: https://libkey.io/10.1177/004912417400300201?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    2. Stephen Johnson, 1967. "Hierarchical clustering schemes," Psychometrika, Springer;The Psychometric Society, vol. 32(3), pages 241-254, September.
    3. R. Luce, 1950. "Connectivity and generalized cliques in sociometric group structure," Psychometrika, Springer;The Psychometric Society, vol. 15(2), pages 169-190, June.
    4. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Richard D. Alba, 1975. "Comment On Mathematical Models In Sociometry," Sociological Methods & Research, , vol. 3(4), pages 489-490, May.
    2. Paul W. Holland & Samuel Leinhardt, 1978. "An Omnibus Test for Social Structure Using Triads," Sociological Methods & Research, , vol. 7(2), pages 227-256, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Noah E. Friedkin, 1984. "Structural Cohesion and Equivalence Explanations of Social Homogeneity," Sociological Methods & Research, , vol. 12(3), pages 235-261, February.
    2. John Daws, 1996. "The analysis of free-sorting data: Beyond pairwise cooccurrences," Journal of Classification, Springer;The Classification Society, vol. 13(1), pages 57-80, March.
    3. Giuseppe Bove & Akinori Okada, 2018. "Methods for the analysis of asymmetric pairwise relationships," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(1), pages 5-31, March.
    4. Simon Blanchard & Wayne DeSarbo & A. Atalay & Nukhet Harmancioglu, 2012. "Identifying consumer heterogeneity in unobserved categories," Marketing Letters, Springer, vol. 23(1), pages 177-194, March.
    5. Michael Rennings & Philipp Baaden & Carolin Block & Marcus John & Stefanie Bröring, 2024. "Assessing emerging sustainability-oriented technologies: the case of precision agriculture," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 2969-2998, June.
    6. Wayne DeSarbo & Vijay Mahajan, 1984. "Constrained classification: The use of a priori information in cluster analysis," Psychometrika, Springer;The Psychometric Society, vol. 49(2), pages 187-215, June.
    7. Shmuel Sattath & Amos Tversky, 1977. "Additive similarity trees," Psychometrika, Springer;The Psychometric Society, vol. 42(3), pages 319-345, September.
    8. Hyunseok Park & Janghyeok Yoon & Kwangsoo Kim, 2012. "Identifying patent infringement using SAO based semantic technological similarities," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 515-529, February.
    9. Nathanaël Randriamihamison & Nathalie Vialaneix & Pierre Neuvial, 2021. "Applicability and Interpretability of Ward’s Hierarchical Agglomerative Clustering With or Without Contiguity Constraints," Journal of Classification, Springer;The Classification Society, vol. 38(2), pages 363-389, July.
    10. Daniel B. McArtor & Gitta H. Lubke & C. S. Bergeman, 2017. "Extending multivariate distance matrix regression with an effect size measure and the asymptotic null distribution of the test statistic," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 1052-1077, December.
    11. Roger Shepard, 1974. "Representation of structure in similarity data: Problems and prospects," Psychometrika, Springer;The Psychometric Society, vol. 39(4), pages 373-421, December.
    12. Giovanna Boccuzzo & Licia Maron, 2017. "Proposal of a composite indicator of job quality based on a measure of weighted distances," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2357-2374, September.
    13. repec:ers:journl:v:xxiv:y:2021:i:4b:p:659-667 is not listed on IDEAS
    14. Kim, Junyung & Shah, Asad Ullah Amin & Kang, Hyun Gook, 2020. "Dynamic risk assessment with bayesian network and clustering analysis," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    15. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves & Lee, Lung-Fei, 2011. "Criminal Networks: Who is the Key Player?," Research Papers in Economics 2011:7, Stockholm University, Department of Economics.
    16. Ma, Jie & Tse, Ying Kei & Wang, Xiaojun & Zhang, Minhao, 2019. "Examining customer perception and behaviour through social media research – An empirical study of the United Airlines overbooking crisis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 192-205.
    17. Muñoz-Mas, Rafael & Vezza, Paolo & Alcaraz-Hernández, Juan Diego & Martínez-Capel, Francisco, 2016. "Risk of invasion predicted with support vector machines: A case study on northern pike (Esox Lucius, L.) and bleak (Alburnus alburnus, L.)," Ecological Modelling, Elsevier, vol. 342(C), pages 123-134.
    18. Gabrielle Demange, 2018. "Contagion in Financial Networks: A Threat Index," Management Science, INFORMS, vol. 64(2), pages 955-970, February.
    19. Lin, Dan & Wu, Jiajing & Xuan, Qi & Tse, Chi K., 2022. "Ethereum transaction tracking: Inferring evolution of transaction networks via link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    20. David G Mets & Michael S Brainard, 2018. "An automated approach to the quantitation of vocalizations and vocal learning in the songbird," PLOS Computational Biology, Public Library of Science, vol. 14(8), pages 1-29, August.
    21. Zhepeng Li & Xiao Fang & Xue Bai & Olivia R. Liu Sheng, 2017. "Utility-Based Link Recommendation for Online Social Networks," Management Science, INFORMS, vol. 63(6), pages 1938-1952, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:somere:v:3:y:1974:i:2:p:123-171. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.