IDEAS home Printed from
   My bibliography  Save this article

Friendly Relationships and Relationships of Assistance at a University



Diliara Valeeva - Research Assistant, International Laboratory for Institutional Analysis of Economic Reforms, National Research University Higher School of Economics. Address: 24 Myasnitskaya str., Moscow, 101000, Russian Federation. E-mail: dvaleeva@hse.ruOleg Poldin - Research Fellow, International Laboratory for Institutional Analysis of Economic Reforms, National Research University Higher School of Economics. Address: 25/12 Bolshaya Pecherskaya str., Nizhny Novgorod, 603155, Russian Federation. E-mail: opoldin@hse.ruMaria Yudkevich - Vice Rector, Director Center for Institutional Studies, National Research University Higher School of Economics. Address: 11 Pokrovskiy blv., Moscow, 109028, Russian Federation. E-mail: yudkevich@hse.ruThe authors explore characteristics of social relationships (friendly relationships and relationships of assistance while studying) between students of the school of economics of one of Russian universities. Within this study fellow students with whom a certain student spends most of his or her time were considered to be his or her friends. An assistant at university is a fellow student whom students ask for help in their studies most of all. Data on a structure of relationships in student groups were collected by means of a questionnaire. In order to analyze a distinction between friendship networks and assistance networks at university, an exponential random graph modeling (ERGM) method was used. The authors show that both networks are characterized by reciprocity of relationships and that in both networks relationships have a tendency to form triads. Probability of a relationship between students depends to a great extent on their belonging to one training group and one sex. Students ask for help and are on friendly terms with those fellow students who have academic achievements of the same level as they do. Academically successful students are popular in the assistance network but not in the friendship network. The received results are analyzed in terms of their meaning for co-education effects. Characteristics of reciprocity of relationships, as well as of their isolation in triads, are important for interpreting the ways the co-education effects can distribute. It looks like the greatest influence on a certain student's achievements his reciprocal friends and assistants can have, and also his immediate environment density. Students studying on a commercial basis are more likely to form friendship networks, while students studying in state-funded places are more likely to form assistance networks. Students of different modes of study seem to build their social relationships in different ways, and so influence of peers on students of different modes of study is different. The authors arrive at a conclusion that in the analysis of co-education effects it is necessary to take into consideration a role different relationships play in distributing these effects, as well as internal features of networks according to which social relationships are built, and also mechanisms of gaining popularity and influence among students.

Suggested Citation

  • Diliara Valeeva & Oleg Poldin & Maria Yudkevich, 2013. "Friendly Relationships and Relationships of Assistance at a University," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 4, pages 70-84.
  • Handle: RePEc:nos:voprob:2013:i:4:p:70-84

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    1. David J. Zimmerman, 2003. "Peer Effects in Academic Outcomes: Evidence from a Natural Experiment," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 9-23, February.
    2. Stanley Wasserman & Philippa Pattison, 1996. "Logit models and logistic regressions for social networks: I. An introduction to Markov graphs andp," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 401-425, September.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. Ekaterina Krekhovets & Oleg Poldin, 2013. "Students' Social Media: Formation Factors and Influence on Studies," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 4, pages 127-144.
    2. Krekhovets, Ekaterina & Poldin, Oleg, 2015. "An empirical analysis of students’ friendship ties formation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 40(4), pages 49-63.

    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. Chih‐Sheng Hsieh & Lung‐Fei Lee & Vincent Boucher, 2020. "Specification and estimation of network formation and network interaction models with the exponential probability distribution," Quantitative Economics, Econometric Society, vol. 11(4), pages 1349-1390, November.
    2. Patacchini, Eleonora & Hsieh, Chih-Sheng & Lin, Xu, 2019. "Social Interaction Methods," CEPR Discussion Papers 14141, C.E.P.R. Discussion Papers.
    3. Ekaterina Krekhovets & Oleg Poldin, 2013. "Students' Social Media: Formation Factors and Influence on Studies," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 4, pages 127-144.
    4. Darolia, Rajeev, 2013. "Integrity versus access? The effect of federal financial aid availability on postsecondary enrollment," Journal of Public Economics, Elsevier, vol. 106(C), pages 101-114.
    5. Maria De Paola & Vincenzo Scoppa, 2010. "Peer group effects on the academic performance of Italian students," Applied Economics, Taylor & Francis Journals, vol. 42(17), pages 2203-2215.
    6. Falk Armin & Kosfeld Michael, 2012. "It's all about Connections: Evidence on Network Formation," Review of Network Economics, De Gruyter, vol. 11(3), pages 1-36, September.
    7. Manuel E. Sosa & Steven D. Eppinger & Craig M. Rowles, 2004. "The Misalignment of Product Architecture and Organizational Structure in Complex Product Development," Management Science, INFORMS, vol. 50(12), pages 1674-1689, December.
    8. B. Jahanshahi, 2014. "Separating Gender Composition Effect from Peer Effects in Education," Working Papers wp932, Dipartimento Scienze Economiche, Universita' di Bologna.
    9. 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.
    10. George R. Goethals & Gordon C. Winston & David J. Zimmerman & Laurie C. Hurshman & Adam C. Sischy & Georgi Zhelev, 2004. "Who Cares? How Students View Faculty and Other Adults in US Higher Education," Williams Project on the Economics of Higher Education DP-67, Department of Economics, Williams College.
    11. SHIMAMOTO Daichi & Yu Ri KIM & TODO Yasuyuki, 2019. "The Effect of Social Interactions on Exporting Activities: Evidence from Micro, Small, and Medium-Sized Enterprises in rural Vietnam," Discussion papers 19020, Research Institute of Economy, Trade and Industry (RIETI).
    12. Song, Yang, 2019. "Sorting, school performance and quality: Evidence from China," Journal of Comparative Economics, Elsevier, vol. 47(1), pages 238-261.
    13. Clifton-Sprigg, Joanna, 2014. "Educational spillovers and parental migration," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-46, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    14. Francesco Agostinelli & Matthias Doepke & Giuseppe Sorrenti & Fabrizio Zilibotti, 2020. "It Takes a Village: The Economics of Parenting with Neighborhood and Peer Effects," Cowles Foundation Discussion Papers 2228, Cowles Foundation for Research in Economics, Yale University.
    15. repec:zbw:rwidps:0002 is not listed on IDEAS
    16. Samrachana Adhikari & Beau Dabbs, 2018. "Social Network Analysis in R: A Software Review," Journal of Educational and Behavioral Statistics, , vol. 43(2), pages 225-253, April.
    17. Yakusheva, Olga & Kapinos, Kandice & Weiss, Marianne, 2011. "Peer effects and the Freshman 15: Evidence from a natural experiment," Economics & Human Biology, Elsevier, vol. 9(2), pages 119-132, March.
    18. Kang, Changhui, 2007. "Classroom peer effects and academic achievement: Quasi-randomization evidence from South Korea," Journal of Urban Economics, Elsevier, vol. 61(3), pages 458-495, May.
    19. Guccio, C. & Lisi, D., 2014. "Social interactions in inappropriate behavior for childbirth services: Theory and evidence from the Italian hospital sector," Health, Econometrics and Data Group (HEDG) Working Papers 14/28, HEDG, c/o Department of Economics, University of York.
    20. Gordon Winston & David Zimmerman, 2004. "Peer Effects in Higher Education," NBER Chapters, in: College Choices: The Economics of Where to Go, When to Go, and How to Pay For It, pages 395-424, National Bureau of Economic Research, Inc.
    21. Jones, Todd R. & Kofoed, Michael S., 2020. "Do peers influence occupational preferences? Evidence from randomly-assigned peer groups at West Point," Journal of Public Economics, Elsevier, vol. 184(C).


    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:nos:voprob:2013:i:4:p:70-84. 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: Marta Morozova (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.