Flow of innovation in deviantArt: following artists on an online social network site


Computer and communication technologies created new modes of creating and sharing arts. In this paper, we apply ‘diffusion of innovation’ theory to investigate how artistic content travels in an online social network site called deviantArt, a site designed for sharing user-generated artworks. We first define what innovation corresponds to in such a context, and then discuss how it can be measured with the help of network, image and text analysis methods. We propose to use user-shared resources as relatively easy targets of tracking innovation.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5


  1. 1.

    SNS are defined as web-based services for users to construct a public or private profile and to connect with other users in a bounded system (Boyd and Ellison 2007). In this sense, dA resembles SNS as it offers basic services to its users, and it creates a community structure. However, dA works like a blog-sphere as well (see Adar et al. 2004 on blogging), as each dA member is bestowed a website on his/her own.

  2. 2.


  3. 3.


  4. 4.

    See Akdag Salah (2010b) for a description on how the promotion mechanism works.


  1. Adar E, Zhang L, Adamic LA, Lukose RM (2004) Implicit structure and the dynamics of blogspace. In: 13th international WWW conference New York: Workshop on the Weblogging Ecosystem

  2. Akdag Salah AA (2010a) The online potential of art creation and dissemination: deviantArt as the next art venue. EVA2010. Computer Arts Society, London

    Google Scholar 

  3. Akdag Salah AA (2010b) Performing curatorial practices in a social network site: The curators of deviantArt. CHArt Conference, London

    Google Scholar 

  4. Akdag Salah A, Salah AA, Buter B, Dijkshoorn N, Modolo D, Nguyen Q, van Noort S, van de Poel B (2012) DeviantArt in spotlight: a network of artists. Leonardo 45(5):486–487

    Google Scholar 

  5. Bikhchandani S, Hirshleifer D, Welch I (1992) A theory of fads, fashion, custom, and cultural change as informational cascades. J Pol Econ 100:992–1026

    Article  Google Scholar 

  6. Boyd DM (2007) Why youth (heart) social network sites: the role of networked publics in teenage social life. In: Buckingham D (ed) Youth, identity, and digital media. MIT Press, Cambridge, pp 119–142

    Google Scholar 

  7. Boyd DM, Ellison NB (2007) Social network sites: definition, history, and scholarship. J Comput Mediat Commun 13(1), article 11

    Google Scholar 

  8. Buter B, Dijkshoorn N, Modolo D, Nguyen Q, van Noort S, van de Poel B, Akdag Salah AA, Salah AA (2011) Explorative visualization and analysis of a social network for arts: The case of deviantArt. J Converg 2(2):87–94

    Google Scholar 

  9. Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. IEEE CVPR WKSHP 886–893

  10. Lee SH, Kim P-J, Jeong H (2006) Statistical properties of sampled networks. PHYS REV E 73

  11. Lewis K, Kaufmann J, Gonzalez M, Wimmer A, Christakis N (2008) Tastes, ties, and time: a new social network dataset using facebook.com. Soc Netw 30:330–342

    Article  Google Scholar 

  12. Liben-Nowell D, Novak J, Kumar R, Raghavan P, Tomkins A (2005) Geographic routing in social networks. PNAS 102(33):11623–11628

    Article  Google Scholar 

  13. Manovich L (2008) Cultural analytics: Analysis and visualization of large cultural data sets. Screen, February: 1–23

  14. Mayer A, Puller SL (2008) The old boy and girl network: social network formation on university campuses. JPBE 92:329–347

    Google Scholar 

  15. Minamikawa A, Yokoyama H (2011) Blog tells what kind of personality you have: egogram estimation from japanese weblog. In: Proceedings of the ACM conference on computer supported cooperative work, pp 217–220

  16. Rogers EM (1976) New product adoption and diffusion. J Consum Res March:290–301

    Google Scholar 

  17. Rogers EM (1995) Diffusion of innovations, 4th edn. Free Press, New York

    Google Scholar 

  18. Rogers EM, Agarwala-Rogers R (1976) Communication in organizations. Free Press, New York

    Google Scholar 

  19. Smeulders AWM, Worring M, Santini S, Gupta A, Jain R (2000) Content-based image retrieval at the end of the early years. IEEE T Pattern Anal 22(12):1349–1380

    Article  Google Scholar 

  20. Snoek CGM, Huurnink B, Hollink L, de Rijke M, Schreiber G, Worring M (2007) Adding semantics to detectors for video retrieval. IEEE T Multimedia 9(5):975–986

    Article  Google Scholar 

  21. Valente TW (1996) Social network thresholds in the diffusion of innovations. Soc Netw. doi:101016/0378-8733(95)00256-1

    Google Scholar 

  22. Valente TW, Davis RL (1999) Accelerating the diffusion of innovations using opinion leaders. Ann Am Acad 566:55–67

    Article  Google Scholar 

  23. Yuan YC, Gay G (2006) Homophily of network ties and bonding and bridging social capital in computer-mediated distributed teams. J Comput Mediat Commun 11(4):1062–1084

    Article  Google Scholar 

Download references


This research is supported by Bogazici University BAP-6531 project and a Nederlandse Organisatie voor Wetenschappelijk Onderzoek NWO-VENI grant.

Author information



Corresponding author

Correspondence to Alkim Almila Akdag Salah.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Akdag Salah, A.A., Salah, A.A. Flow of innovation in deviantArt: following artists on an online social network site. Mind Soc 12, 137–149 (2013). https://doi.org/10.1007/s11299-013-0113-9

Download citation


  • Art market
  • Social network sites
  • Complex networks
  • Image analysis
  • Text analysis