The DOI matches its Crossref record; 72 of the 72 references it cites were found in a registry or an index.
Social Networks and the Diffusion of User-Generated Content: Evidence from YouTube
Abstract
This paper is motivated by the success of YouTube, which is attractive to content creators as well as corporations for its potential to rapidly disseminate digital content. The networked structure of interactions on YouTube and the tremendous variation in the success of videos posted online lends itself to an inquiry of the role of social influence. Using a unique data set of video information and user information collected from YouTube, we find that social interactions are influential not only in determining which videos become successful but also on the magnitude of that impact. We also find evidence for a number of mechanisms by which social influence is transmitted, such as (i) a preference for conformity and homophily and (ii) the role of social networks in guiding opinion formation and directing product search and discovery. Econometrically, the problem in identifying social influence is that individuals' choices depend in great part upon the choices of other individuals, referred to as the reflection problem. Another problem in identification is to distinguish between social contagion and user heterogeneity in the diffusion process. Our results are in sharp contrast to earlier models of diffusion, such as the Bass model, that do not distinguish between different social processes that are responsible for the process of diffusion. Our results are robust to potential self-selection according to user tastes, temporal heterogeneity and the reflection problem. Implications for researchers and managers are discussed.
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Granovetter, M. S. (1973) · American Journal of Sociology · doi:10.1086/225469 · Cited by 40,491
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2019) · An Integrated Approach to Communication Theory and Research · doi:10.4324/9780203710753-35 · Cited by 37,322
Bowling alone: the collapse and revival of American community
(2000) · Choice Reviews Online · doi:10.5860/choice.38-2454 · Cited by 28,789
(2001) · RePEc: Research Papers in Economics · Cited by 27,577
The Structure and Function of Complex Networks
Newman, M. E. J. (2003) · SIAM Review · doi:10.1137/s003614450342480 · Cited by 18,719
Social Network Analysis: Methods and Applications
Wasserman, S. S., & Faust, K. (1994) · Cited by 17,961
Social Network Analysis: Methods and Applications
Wasserman, S., & Faust, K. (1994) · doi:10.1017/cbo9780511815478 · Cited by 17,557
Putnam, R. (2000) · doi:10.1145/358916.361990 · Cited by 17,114
Centrality in social networks conceptual clarification
Freeman, L. C. (1978) · Social Networks · doi:10.1016/0378-8733(78)90021-7 · Cited by 17,062
Burt, R. S. (1992) · doi:10.4159/9780674029095 · Cited by 9,093
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Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013) · MIS Quarterly · doi:10.25300/misq/2013/37:2.3 · Cited by 4,392
Organizing for Innovation in the Digitized World
Yoo, Y., Boland, R. J., Lyytinen, K., & Majchrzak, A. (2012) · Organization Science · doi:10.1287/orsc.1120.0771 · Cited by 2,469
Lin, M., Prabhala, N. R., & Viswanathan, S. (2013) · Management Science · doi:10.1287/mnsc.1120.1560 · Cited by 1,299
Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook
Lee, D., Hosanagar, K., & Nair, H. S. (2018) · Management Science · doi:10.1287/mnsc.2017.2902 · Cited by 1,069
Managing Brands in the Social Media Environment
Gensler, S., Völckner, F., Liu-Thompkins, Y., & Wiertz, C. (2013) · Journal of Interactive Marketing · doi:10.1016/j.intmar.2013.09.004 · Cited by 911
Metadata
- Authors
- Susarla, A., Oh, J.-H., & Tan, Y.
- Venue
- Information Systems Research
- Published
- 2012-03
- Volume
- 23
- Issue
- 1
- Pages
- 23-41
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W2120131867
- Cited by
- 630
- References
- 72
- FWCI
- 22.90
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.