IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v420y2015icp148-163.html
   My bibliography  Save this article

Homophyly/kinship hypothesis: Natural communities, and predicting in networks

Author

Listed:
  • Li, Angsheng
  • Li, Jiankou
  • Pan, Yicheng

Abstract

It has been a longstanding challenge to understand natural communities in real world networks. We proposed a community finding algorithm based on fitness of networks, two algorithms for prediction, accurate prediction and confirmation of keywords for papers in the citation network Arxiv HEP-TH (high energy physics theory), and the measures of internal centrality, external de-centrality, internal and external slopes to characterize the structures of communities. We implemented our algorithms on 2 citation and 5 cooperation graphs. Our experiments explored and validated a homophyly/kinship principle of real world networks. The homophyly/kinship principle includes: (1) homophyly is the natural selection in real world networks, similar to Darwin’s kinship selection in nature, (2) real world networks consist of natural communities generated by the natural selection of homophyly, (3) most individuals in a natural community share a short list of common attributes, (4) natural communities have an internal centrality (or internal heterogeneity) that a natural community has a few nodes dominating most of the individuals in the community, (5) natural communities have an external de-centrality (or external homogeneity) that external links of a natural community homogeneously distributed in different communities, and (6) natural communities of a given network have typical structures determined by the internal slopes, and have typical patterns of outgoing links determined by external slopes, etc. Our homophyly/kinship principle perfectly matches Darwin’s observation that animals from ants to people form social groups in which most individuals work for the common good, and that kinship could encourage altruistic behavior. Our homophyly/kinship principle is the network version of Darwinian theory, and builds a bridge between Darwinian evolution and network science.

Suggested Citation

  • Li, Angsheng & Li, Jiankou & Pan, Yicheng, 2015. "Homophyly/kinship hypothesis: Natural communities, and predicting in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 148-163.
  • Handle: RePEc:eee:phsmap:v:420:y:2015:i:c:p:148-163
    DOI: 10.1016/j.physa.2014.10.082
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437114009376
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2014.10.082?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sanjeev Goyal & Marco J. van der Leij & José Luis Moraga-Gonzalez, 2006. "Economics: An Emerging Small World," Journal of Political Economy, University of Chicago Press, vol. 114(2), pages 403-432, April.
    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. Li, Angsheng & Li, Jiankou & Pan, Yicheng, 2015. "Discovering natural communities in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 878-896.

    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. Katharina Rath & Klaus Wohlrabe, 2016. "Recent trends in co-authorship in economics: evidence from RePEc," Applied Economics Letters, Taylor & Francis Journals, vol. 23(12), pages 897-902, August.
    2. Lorenzo Ductor & Sanjeev Goyal & Anja Prummer, 2018. "Gender & Collaboration," Working Papers 856, Queen Mary University of London, School of Economics and Finance.
    3. Cilem Selin Hazir & Corinne Autant-Bernard, 2012. "Using Affiliation Networks to Study the Determinants of Multilateral Research Cooperation Some empirical evidence from EU Framework Programs in biotechnology," Working Papers 1212, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    4. Carillo, Maria Rosaria & Papagni, Erasmo & Sapio, Alessandro, 2013. "Do collaborations enhance the high-quality output of scientific institutions? Evidence from the Italian Research Assessment Exercise," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 47(C), pages 25-36.
    5. Nicolás Ajzenman & Bruno Ferman & Sant’Anna Pedro C., 2023. "Discrimination in the Formation of Academic Networks: A Field Experiment on #EconTwitter," Working Papers 235, Red Nacional de Investigadores en Economía (RedNIE).
    6. Rosamaria d’Amore & Roberto Iorio & Agnieszka Stawinoga, 2011. "Who and where are the co-authors? The relationship between institutional and geographical distance in scientific publications," Working Papers 2011.4, International Network for Economic Research - INFER.
    7. Michael E. Rose, 2022. "Small world: Narrow, wide, and long replication of Goyal, van der Leij and Moraga‐Gonzélez (JPE 2006) and a comparison of EconLit and Scopus," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 820-828, June.
    8. Tao, Qizhi & Li, Haoyu & Wu, Qun & Zhang, Ting & Zhu, Yingjun, 2019. "The dark side of board network centrality: Evidence from merger performance," Journal of Business Research, Elsevier, vol. 104(C), pages 215-232.
    9. Nora, Vladyslav & Winter, Eyal, 2024. "Exploiting social influence in networks," Theoretical Economics, Econometric Society, vol. 19(1), January.
    10. João Faria & Rajeev Goel, 2010. "Returns to networking in academia," Netnomics, Springer, vol. 11(2), pages 103-117, July.
    11. Ying Chen & Tom Lane & Stuart McDonald, 2023. "Endogenous Network Formation in Local Public Goods: An Experimental Analysis," Discussion Papers 2023-02, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    12. De Silva, Dakshina G. & Gertsberg, Marina & Kosmopoulou, Georgia & Pownall, Rachel A.J., 2022. "Evolution of a dealer trading network and its effects on art auction prices," European Economic Review, Elsevier, vol. 144(C).
    13. Sanjeev Goyal & Marco J. van der Leij & José Luis Moraga-Gonzalez, 2006. "Economics: An Emerging Small World," Journal of Political Economy, University of Chicago Press, vol. 114(2), pages 403-432, April.
    14. Cowan, Robin & Jonard, Nicolas & Sanditov, Bulat, 2009. "Fits and Misfits: Technological Matching and R&D Networks," MERIT Working Papers 2009-042, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    15. Martin Steininger & Bernd Süssmuth, 2005. "Elfenbeinligen und ihre Erfassung: Ein Kommentar und eine neuerliche Messung der Publikationstätigkeit der Wirtschaftsforschungsinstitute im deutschsprachigen Raum: 1989–2003," Perspektiven der Wirtschaftspolitik, Verein für Socialpolitik, vol. 6(3), pages 409-420, August.
    16. de Marti, Joan & Zenou, Yves, 2009. "Social Networks," Working Paper Series 816, Research Institute of Industrial Economics.
    17. Carayol, Nicolas & Roux, Pascale, 2009. "Knowledge flows and the geography of networks: A strategic model of small world formation," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 414-427, August.
    18. Andrea Galeotti & Benjamin Golub & Sanjeev Goyal, 2020. "Targeting Interventions in Networks," Econometrica, Econometric Society, vol. 88(6), pages 2445-2471, November.
    19. Lorenzo Napolitano & Evangelos Evangelou & Emanuele Pugliese & Paolo Zeppini & Graham Room, 2017. "Technology networks: the autocatalytic origins of innovation," Papers 1708.03511, arXiv.org, revised Apr 2018.
    20. Hendrik P. Van Dalen & Arjo Klamer, 2005. "Is Science A Case of Wasteful Competition?," Kyklos, Wiley Blackwell, vol. 58(3), pages 395-414, July.

    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:eee:phsmap:v:420:y:2015:i:c:p:148-163. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.