Skip to main content

Core But Not Peripheral Online Social Ties is a Protective Factor Against Depression: Evidence from a Nationally Representative Sample of Young Adults

  • Conference paper
  • First Online:
Network Science (NetSci-X 2022)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 13197))

Included in the following conference series:

  • 503 Accesses

Abstract

As social interactions are increasingly taking place in the digital environment, online friendship and its effects on various life outcomes from health to happiness attract growing research attention. In most studies, online ties are treated as representing a single type of relationship. However, our online friendship networks are not homogeneous and could include close connections, e.g. a partner, as well as people we have never met in person. In this paper, we investigate the potentially differential effects of online friendship ties on mental health. Using data from a Russian panel study (\(N = 4,400\)), we find that - consistently with previous research - the number of online friends correlates with depression symptoms. However, this is true only for networks that do not exceed Dunbar’s number in size (\(N \le 150\)) and only for core but not peripheral nodes of a friendship network. The findings suggest that online friendship could encode different types of social relationships that should be treated separately while investigating the association between online social integration and life outcomes, in particular well-being or mental health.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 44.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 59.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Albert, R., Barabási, A.L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74(1), 47 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  2. Appel, H., Gerlach, A.L., Crusius, J.: The interplay between Facebook use, social comparison, envy, and depression. Curr. Opin. Psychol. 9, 44–49 (2016)

    Article  Google Scholar 

  3. van Beljouw, I.M., Verhaak, P.F., Cuijpers, P., van Marwijk, H.W., Penninx, B.W.: The course of untreated anxiety and depression, and determinants of poor one-year outcome: a one-year cohort study. BMC Psychiatry 10(1), 1–10 (2010)

    Google Scholar 

  4. Borgatti, S.P., Everett, M.G.: Models of core/periphery structures. Soc. Netw. 21(4), 375–395 (2000)

    Article  Google Scholar 

  5. Brody, D.J., Pratt, L.A., Hughes, J.P.: Prevalence of depression among adults aged 20 and over: United states, 2013–2016. NCHS Data Brief 303, 1–8 (2018)

    Google Scholar 

  6. Burdzovic Andreas, J., Brunborg, G.S.: Depressive symptomatology among Norwegian adolescent boys and girls: the patient health questionnaire-9 (PHQ-9) psychometric properties and correlates. Front. Psychol. 8, 887 (2017)

    Article  Google Scholar 

  7. Cattani, G., Ferriani, S.: A core/periphery perspective on individual creative performance: social networks and cinematic achievements in the hollywood film industry. Organ. Sci. 19(6), 824–844 (2008)

    Article  Google Scholar 

  8. Choi, K.W., et al.: An exposure-wide and mendelian randomization approach to identifying modifiable factors for the prevention of depression. Am. J. Psychiatry 177(10), 944–954 (2020)

    Article  Google Scholar 

  9. Choi, M., Aiello, L.M., Varga, K.Z., Quercia, D.: Ten social dimensions of conversations and relationships. In: Proceedings of the Web Conference 2020, pp. 1514–1525 (2020)

    Google Scholar 

  10. Chou, H.T.G., Edge, N.: “They are happier and having better lives than I am’’: the impact of using Facebook on perceptions of others’ lives. Cyberpsychol. Behav. Soc. Netw. 15(2), 117–121 (2012)

    Article  Google Scholar 

  11. Coyne, J.C.: Depression and the response of others. J. Abnorm. Psychol. 85(2), 186 (1976)

    Article  Google Scholar 

  12. Da Silva, M.R., Ma, H., Zeng, A.P.: Centrality, network capacity, and modularity as parameters to analyze the core-periphery structure in metabolic networks. Proc. IEEE 96(8), 1411–1420 (2008)

    Article  Google Scholar 

  13. Dunbar, R.I.: Neocortex size as a constraint on group size in primates. J. Hum. Evol. 22(6), 469–493 (1992)

    Article  Google Scholar 

  14. Dunbar, R.I.: The social brain hypothesis. Evol. Anthropol. Issues News Rev. 6(5), 178–190 (1998)

    Article  Google Scholar 

  15. Dunbar, R.I., Arnaboldi, V., Conti, M., Passarella, A.: The structure of online social networks mirrors those in the offline world. Soc. Netw. 43, 39–47 (2015)

    Article  Google Scholar 

  16. Eisenberg, D., Gollust, S.E., Golberstein, E., Hefner, J.L.: Prevalence and correlates of depression, anxiety, and suicidality among university students. Am. J. Orthopsychiatry 77(4), 534–542 (2007)

    Article  Google Scholar 

  17. Elmer, T., Boda, Z., Stadtfeld, C.: The co-evolution of emotional well-being with weak and strong friendship ties. Netw. Sci. 5(3), 278–307 (2017)

    Article  Google Scholar 

  18. Elmer, T., Stadtfeld, C.: Depressive symptoms are associated with social isolation in face-to-face interaction networks. Sci. Rep. 10(1), 1–12 (2020)

    Article  Google Scholar 

  19. Fatiregun, A., Kumapayi, T.: Prevalence and correlates of depressive symptoms among in-school adolescents in a rural district in Southwest Nigeria. J. Adolesc. 37(2), 197–203 (2014)

    Article  Google Scholar 

  20. Feinstein, B.A., Hershenberg, R., Bhatia, V., Latack, J.A., Meuwly, N., Davila, J.: Negative social comparison on Facebook and depressive symptoms: rumination as a mechanism. Psychol. Pop. Media Cult. 2(3), 161 (2013)

    Article  Google Scholar 

  21. Fingerman, K.L.: Consequential strangers and peripheral ties: the importance of unimportant relationships. J. Family Theory Rev. 1(2), 69–86 (2009)

    Article  Google Scholar 

  22. Fiore, J., Becker, J., Coppel, D.B.: Social network interactions: a buffer or a stress. Am. J. Community Psychol. 11(4), 423 (1983)

    Article  Google Scholar 

  23. Ganguly, S., Samanta, M., Roy, P., Chatterjee, S., Kaplan, D.W., Basu, B.: Patient health questionnaire-9 as an effective tool for screening of depression among Indian adolescents. J. Adolesc. Health 52(5), 546–551 (2013)

    Article  Google Scholar 

  24. Gonçalves, B., Perra, N., Vespignani, A.: Modeling users’ activity on Twitter networks: validation of Dunbar’s number. PLoS ONE 6(8), e22656 (2011)

    Article  Google Scholar 

  25. Granovetter, M.S.: The strength of weak ties. Am. J. Sociol. 78(6), 1360–1380 (1973)

    Article  Google Scholar 

  26. Hays, J.C., Steffens, D.C., Flint, E.P., Bosworth, H.B., George, L.K.: Does social support buffer functional decline in elderly patients with unipolar depression? Am. J. Psychiatry 158(11), 1850–1855 (2001)

    Article  Google Scholar 

  27. Hill, R.A., Dunbar, R.I.: Social network size in humans. Hum. Nat. 14(1), 53–72 (2003)

    Article  Google Scholar 

  28. Hobbs, W.R., Burke, M., Christakis, N.A., Fowler, J.H.: Online social integration is associated with reduced mortality risk. Proc. Natl. Acad. Sci. 113(46), 12980–12984 (2016)

    Article  Google Scholar 

  29. Kawachi, I., Berkman, L.F.: Social ties and mental health. J. Urban Health 78(3), 458–467 (2001)

    Article  Google Scholar 

  30. Kojaku, S., Xu, M., Xia, H., Masuda, N.: Multiscale core-periphery structure in a global liner shipping network. Sci. Rep. 9(1), 1–15 (2019)

    Article  Google Scholar 

  31. Kroenke, K., Strine, T.W., Spitzer, R.L., Williams, J.B., Berry, J.T., Mokdad, A.H.: The PHQ-8 as a measure of current depression in the general population. J. Affect. Disord. 114(1–3), 163–173 (2009)

    Article  Google Scholar 

  32. Latkin, C.A., Edwards, C., Davey-Rothwell, M.A., Tobin, K.E.: The relationship between social desirability bias and self-reports of health, substance use, and social network factors among urban substance users in Baltimore, Maryland. Addict. Behav. 73, 133–136 (2017)

    Article  Google Scholar 

  33. Liu, S., et al.: Online mental health services in China during the Covid-19 outbreak. Lancet Psychiatry 7(4), e17–e18 (2020)

    Article  Google Scholar 

  34. Lup, K., Trub, L., Rosenthal, L.: Instagram# instasad?: exploring associations among Instagram use, depressive symptoms, negative social comparison, and strangers followed. Cyberpsychol. Behav. Soc. Netw. 18(5), 247–252 (2015)

    Article  Google Scholar 

  35. Luppa, M., et al.: Age-and gender-specific prevalence of depression in latest-life-systematic review and meta-analysis. J. Affect. Disord. 136(3), 212–221 (2012)

    Article  Google Scholar 

  36. Malik, V.: The Russian panel study ‘trajectories in education and careers’. Longitudinal Life Course Stud. 10(1), 125–144 (2019)

    Article  Google Scholar 

  37. Masuda, N., Kurahashi, I., Onari, H.: Suicide ideation of individuals in online social networks. PLoS ONE 8(4), e62262 (2013)

    Article  Google Scholar 

  38. Mikolajczyk, R.T., et al.: Prevalence of depressive symptoms in university students from Germany, Denmark, Poland and Bulgaria. Soc. Psychiatry Psychiatr. Epidemiol. 43(2), 105–112 (2008)

    Google Scholar 

  39. Negriff, S.: Depressive symptoms predict characteristics of online social networks. J. Adolesc. Health 65(1), 101–106 (2019)

    Article  Google Scholar 

  40. OECD: PISA 2012 Results: What Students Know and Can Do. Student Performance in Mathematics, Reading and Science. OECD Publishing (2014)

    Google Scholar 

  41. Overgoor, J., Adamic, L.A., et al.: The structure of US college networks on Facebook. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 14, pp. 499–510 (2020)

    Google Scholar 

  42. Park, S., Lee, S.W., Kwak, J., Cha, M., Jeong, B.: Activities on Facebook reveal the depressive state of users. J. Med. Internet Res. 15(10), e217 (2013)

    Article  Google Scholar 

  43. Public Opinion Foundation: Online practices of Russians: social networks (2016). http://fom.ru/SMI-i-internet/12495. Accessed 09 Sep 2021

  44. Richardson, L.P., et al.: Evaluation of the patient health questionnaire-9 item for detecting major depression among adolescents. Pediatrics 126(6), 1117–1123 (2010)

    Article  Google Scholar 

  45. Schaefer, D.R., Kornienko, O., Fox, A.M.: Misery does not love company: network selection mechanisms and depression homophily. Am. Sociol. Rev. 76(5), 764–785 (2011)

    Article  Google Scholar 

  46. Seidman, S.B.: Network structure and minimum degree. Soc. Netw. 5(3), 269–287 (1983)

    Article  MathSciNet  Google Scholar 

  47. Smirnov, I., Sivak, E., Kozmina, Y.: In search of lost profiles. Educ. Stud. Moscow 4, 106–122 (2016)

    Google Scholar 

  48. Steers, M.L.N., Wickham, R.E., Acitelli, L.K.: Seeing everyone else’s highlight reels: how Facebook usage is linked to depressive symptoms. J. Soc. Clin. Psychol. 33(8), 701–731 (2014)

    Article  Google Scholar 

  49. Taylor, H.O., Taylor, R.J., Nguyen, A.W., Chatters, L.: Social isolation, depression, and psychological distress among older adults. J. Aging Health 30(2), 229–246 (2018)

    Article  Google Scholar 

  50. Thoits, P.A.: Mechanisms linking social ties and support to physical and mental health. J. Health Soc. Behav. 52(2), 145–161 (2011)

    Article  Google Scholar 

  51. Tsai, F.J., Huang, Y.H., Liu, H.C., Huang, K.Y., Huang, Y.H., Liu, S.I.: Patient health questionnaire for school-based depression screening among Chinese adolescents. Pediatrics 133(2), e402–e409 (2014)

    Article  Google Scholar 

  52. Ueno, K.: The effects of friendship networks on adolescent depressive symptoms. Soc. Sci. Res. 34(3), 484–510 (2005)

    Article  Google Scholar 

  53. Ugander, J., Karrer, B., Backstrom, L., Marlow, C.: The anatomy of the Facebook social graph. arXiv preprint arXiv:1111.4503 (2011)

  54. Vedula, N., Parthasarathy, S.: Emotional and linguistic cues of depression from social media. In: Proceedings of the 2017 International Conference on Digital Health, pp. 127–136 (2017)

    Google Scholar 

  55. Wang, Q., Gao, J., Zhou, T., Hu, Z., Tian, H.: Critical size of ego communication networks. EPL (Europhys. Lett.) 114(5), 58004 (2016)

    Article  Google Scholar 

  56. Wasserman, S., Faust, K., et al.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)

    Book  MATH  Google Scholar 

  57. Wiederhold, B.K.: Connecting through technology during the coronavirus disease 2019 pandemic: avoiding “Zoom Fatigue’’. Cyberpsychol. Behav. Soc. Netw. 23(7), 437–438 (2020)

    Article  Google Scholar 

Download references

Acknowledgment

This work was supported by a grant from the Russian Science Foundation (project number 19-18-00271).

The data of the Russian panel study “Trajectories in Education and Career” (TrEC http://trec.hse.ru/) is presented in this work. The TrEC project is supported by the Basic Research Programme of the National Research University Higher School of Economics.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sofia Dokuka .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dokuka, S., Sivak, E., Smirnov, I. (2022). Core But Not Peripheral Online Social Ties is a Protective Factor Against Depression: Evidence from a Nationally Representative Sample of Young Adults. In: Ribeiro, P., Silva, F., Mendes, J.F., Laureano, R. (eds) Network Science. NetSci-X 2022. Lecture Notes in Computer Science(), vol 13197. Springer, Cham. https://doi.org/10.1007/978-3-030-97240-0_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-97240-0_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-97239-4

  • Online ISBN: 978-3-030-97240-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics