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Disentangling the Effects of Social Network Density on Electronic Word-of-Mouth (eWOM) Intention
Open accessAbstract
A widely accepted notion in diffusion literature is that individuals’ word-of-mouth behavior is constrained by the properties of social structures (e.g., tie strength, positions in a network) they belong to. Although many studies have indeed confirmed the existence of such social influence, little is known about how the social structural effects are produced and work at a psychological level. This study attempts to present how one's electronic word-of-mouth (eWOM) intention is shaped by 2 key factors—the valence of product-related information and the social coherence of the communication network in which s/he belongs. To understand the process through which the network structures moderate the impact of information valence on eWOM intention, 2 different moderation processes—a) mediated moderation and b) moderated mediation—were tested in a 2 × 2 factorial experiment. The experimental results supported the moderated mediation model, and the implications of the results were discussed.
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“Social network analysis has been researched in relation to electronic word-of-mouth (Sohn, 2009), identifying influencers (Zhang & Li, 2014) and investigating how individuals influence others, the relationship between influence and tie strength and the flow of information through social media (Gandomi & Haider, 2015).”
From Setting the future of digital and social media marketing research: Perspectives and research propositions (2021) · cites this paper as Sohn, 2009
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Cites
Baron, R. M., & Kenny, D. A. (1986) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.51.6.1173 · Cited by 91,532
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) · Routledge eBooks · doi:10.4324/9780203710753-35 · Cited by 37,670
Valente, T. W. (2003) · Genetics in Medicine · doi:10.1097/01.gim.0000061743.67794.c4 · Cited by 20,559
Social Network Analysis: Methods and Applications
Wasserman, S. S., & Faust, K. (1994) · Cited by 18,005
Social Network Analysis: Methods and Applications
Wasserman, S., & Faust, K. (1994) · doi:10.1017/cbo9780511815478 · Cited by 17,557
Measuring the involvement construct
Zaichkowsky, J. L. (1985) · Journal of Consumer Research · doi:10.1086/208520 · Cited by 6,013
Social Network Analysis: A Handbook.
Pappi, F. U., & Scott, J. P. (1993) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2075047 · Cited by 5,964
Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004) · Journal of Interactive Marketing · doi:10.1002/dir.10073 · Cited by 5,916
(1978) · Cited by 5,009
RATIONAL CHOICE AND THE FRAMING OF DECISIONS
Tversky, A., & Kahneman, D. J. (1988) · Cambridge University Press eBooks · doi:10.1017/cbo9780511598951.011 · Cited by 3,733
Getting a Job: A Study of Contacts and Careers.
Hallinan, M. T., & Granovetter, M. S. (1975) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2063210 · Cited by 3,702
Rational Choice and the Framing of Decisions
Tversky, A., & Kahneman, D. J. (1986) · The Journal of Business · doi:10.1086/296365 · Cited by 3,638
When moderation is mediated and mediation is moderated.
Müller, D., Judd, C. M., & Yzerbyt, V. Y. (2005) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.89.6.852 · Cited by 3,435
Social Contagion and Innovation: Cohesion versus Structural Equivalence
Burt, R. S. (1987) · American Journal of Sociology · doi:10.1086/228667 · Cited by 2,421
Social Ties and Word-of-Mouth Referral Behavior
Brown, J. J., & Reingen, P. H. (1987) · Journal of Consumer Research · doi:10.1086/209118 · Cited by 2,388
Marsden, P. V. (1990) · Annual Review of Sociology · doi:10.1146/annurev.so.16.080190.002251 · Cited by 2,224
Feldman, J. M., & Lynch, J. G. (1988) · Journal of Applied Psychology · doi:10.1037/0021-9010.73.3.421 · Cited by 2,070
Diffusion of Innovations, 5th Edition
Rogers, E. M., Simon, 。., & Schuster (2003) · Cited by 2,049
Mediators, moderators, and tests for mediation.
James, L. R., & Brett, J. M. (1984) · Journal of Applied Psychology · doi:10.1037/0021-9010.69.2.307 · Cited by 1,662
Phelps, J. E., Lewis, R. M., Mobilio, L. J., Perry, D. K., & Raman, N. (2004) · Journal of Advertising Research · doi:10.1017/s0021849904040371 · Cited by 940
Grewal, D., Gotlieb, J. B., & Marmorstein, H. (1994) · Journal of Consumer Research · doi:10.1086/209388 · Cited by 797
Online Word-of-Mouth (or Mouse): An Exploration of Its Antecedents and Consequences
Sun, T., Youn, S., Wu, G., & Kuntaraporn, M. (2006) · Journal of Computer-Mediated Communication · doi:10.1111/j.1083-6101.2006.00310.x · Cited by 646
Olney, T. J., Holbrook, M. B., & Batra, R. (1991) · Journal of Consumer Research · doi:10.1086/208569 · Cited by 564
An Attribution Explanation of the Disproportionate Influence of Unfavorable Information
Mizerski, R. W. (1982) · Journal of Consumer Research · doi:10.1086/208925 · Cited by 560
Structure, Cooperation, and the Flow of Market Information
Frenzen, J., & Nakamoto, K. (1993) · Journal of Consumer Research · doi:10.1086/209355 · Cited by 425
Word-of-mouth Communication by the Innovator
Engel, J. F., Kegerreis, R. J., & Blackwell, R. D. (1969) · Journal of Marketing · doi:10.1177/002224296903300303 · Cited by 351
Message Framing and Persuasion: A Message Processing Analysis
Smith, S. M., & Petty, R. E. (1996) · Personality and Social Psychology Bulletin · doi:10.1177/0146167296223004 · Cited by 341
Yong, Z., & Buda, R. (1999) · Journal of Advertising · doi:10.1080/00913367.1999.10673580 · Cited by 321
Richins, M. L., & Shaffer, T. R. (1988) · ACR North American Advances · Cited by 288
Taboo Trade‐Offs, Relational Framing, and the Acceptability of Exchanges
McGraw, A. P., & Tetlock, P. E. (2005) · Journal of Consumer Psychology · doi:10.1207/s15327663jcp1501_2 · Cited by 257
On the Importance of Marginality: One More Step into the Two-Step Flow of Communication
Weimann, G. (1982) · American Sociological Review · doi:10.2307/2095212 · Cited by 243
Free Riders and Zealots: The Role of Social Networks
Coleman, J. S. (1988) · Sociological Theory · doi:10.2307/201913 · Cited by 204
Electronic Word-of-Mouth in Online Environments
Vilpponen, A., Winter, S., & Sundqvist, S. (2006) · Journal of Interactive Advertising · doi:10.1080/15252019.2006.10722120 · Cited by 151
Integrating individual, relational and structural analysis
Wellman, B., Frank, O., Espinoza, V., et al. (1991) · Social Networks · doi:10.1016/0378-8733(91)90007-g · Cited by 86
Robben, H. S. J., & Verhallen, T. M. M. (1994) · Journal of Economic Psychology · doi:10.1016/0167-4870(94)90008-6 · Cited by 62
Motives Underlying Marketing Information Acquisition and Knowledge Transfer
Hirschman, E. C., & Wallendorf, M. (1982) · Journal of Advertising · doi:10.1080/00913367.1982.10672809 · Cited by 52
Online Discussion Groups as Socal Networks
Steyer, A., Garcia‐Bardidia, R., & Quester, P. G. (2006) · Journal of Interactive Advertising · doi:10.1080/15252019.2006.10722118 · Cited by 39
Communication Dilemmas in Social Networks: An Experimental Study
Bonacich, P. (1990) · American Sociological Review · doi:10.2307/2095768 · Cited by 37
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Dwivedi, Y. K., Ismagilova, E., Hughes, D. L., Carlson, J., Filieri, R., Jacobson, J., Jain, V., Karjaluoto, H., Kefi, H., Krishen, A. S., et al. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102168 · Cited by 4,608
“Social network analysis has been researched in relation to electronic word-of-mouth (Sohn, 2009), identifying influencers (Zhang & Li, 2014) and investigating how individuals influence others, the relationship between influence and tie strength and the flow of information through social media…”
BackgroundHayes, J. L., Brinson, N. H., Bott, G. J., & Moeller, C. M. (2021) · Journal of Interactive Marketing · doi:10.1016/j.intmar.2021.01.001 · Cited by 180
Metadata
- Authors
- Sohn, D.
- Affiliations
- The Ohio State University (US)
- Corresponding author
- Sohn, Dongyoung
- ORCID
- Sohn, Dongyoung
- Venue
- Journal of Computer-Mediated Communication
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-01
- Volume
- 14
- Issue
- 2
- Pages
- 352-367
- ISSN
- 1083-6101 (ISSN-L)
- OpenAlex
- W2089946080
- Cited by
- 98
- References
- 39
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 6 · 2023: 7 · 2022: 4 · 2021: 2 · 2020: 10 · 2019: 7 · 2018: 6 · 2017: 9 · 2016: 10 · 2015: 3 · 2014: 8 · 2013: 2 · 2012: 3
- FWCI
- 16.24
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Computer-Mediated Communication (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Social Sciences › Decision Sciences › Information Systems and Management › Knowledge Management and Sharing
- Keywords
- electronic word of mouth, social network density, social influence, information valence, social coherence, moderated mediation, diffusion of innovations, social structure
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