The DOI matches its Crossref record.
Social Network Analysis: Methods and Applications
Abstract
Social network analysis is used widely in the social and behavioral sciences, as well as in economics, marketing, and industrial engineering. The social network perspective focuses on relationships among social entities and is an important addition to standard social and behavioral research, which is primarily concerned with attributes of the social units. Social Network Analysis: Methods and Applications reviews and discusses methods for the analysis of social networks with a focus on applications of these methods to many substantive examples. It is a reference book that can be used by those who want a comprehensive review of network methods, or by researchers who have gathered network data and want to find the most appropriate method by which to analyze it. It is also intended for use as a textbook as it is the first book to provide comprehensive coverage of the methodology and applications of the field.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Social network data were collected using widely accepted sociometric techniques (Wasserman and Faust 1994).”
From Enterprise System Implementation and Employee Job Performance: Understanding the Role of Advice Networks1 (2014) · cites this paper as Wasserman and Faust 1994
In the citing paper
“These include degree centrality, 5 https://qgis.org/api/qgsalgorithmextractbylocation_8h_source.html closeness centrality, and betweenness centrality (Wasserman and Faust, 1994;Freeman, 1979.”
From POI VizNet: New QGIS Tool to construct Visibility Networks in Cities (2024) · cites this paper as Wasserman and Faust, 1994
In the citing paper
“Network analysis metrics come in two flavours, global and local (Wasserman and Faust 1994;Collar et al. 2015).”
From Modelling of pathways and movement networks in archaeology: an overview of current approaches (2019) · cites this paper as Wasserman and Faust 1994
In the citing paper
“Firms may gain such an understanding by using social network analysis (Wasserman and Faust 1994), value blueprints (Adner 2012), or agent-based modeling (Gilbert 2008).”
From Stakeholder marketing: theoretical foundations and required capabilities (2015) · cites this paper as Wasserman and Faust 1994
Citations
Cited by
Sorted by citations
Items 1,001–1,053 of 1,053
Schoon, E. W. (2022) · American Sociological Review · doi:10.1177/00031224221081379 · Cited by 143
Miranda-Dominguez, O., Mills, B. D., Grayson, D., Woodall, A., Grant, K. A., Kroenke, C. D., & Fair, D. A. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.4229-13.2014 · Cited by 130
“A node with high degree will have strong, direct connections to many other nodes in the network (Wasserman and Faust, 1994; Bullmore and Sporns, 2009).”
BackgroundA Comparison of Social Organization in Asian Elephants and African Savannah Elephants
de Silva, S., & Wittemyer, G. (2012) · International Journal of Primatology · doi:10.1007/s10764-011-9564-1 · Cited by 134
Better with Age? Tie Longevity and the Performance Implications of Bridging and Closure
Baum, J. A. C., McEvily, B., & Rowley, T. J. (2012) · Organization Science · doi:10.1287/orsc.1100.0566 · Cited by 133
Insider Threat Detection Based on User Behavior Modeling and Anomaly Detection Algorithms
Kim, J., Park, M., Kim, H., Cho, S., & Kang, P. (2019) · Applied Sciences · doi:10.3390/app9194018 · Cited by 134
Systematic Review of Social Network Analysis in Adolescent Cigarette Smoking Behavior*
Seo, D., & Huang, Y. (2012) · Journal of School Health · doi:10.1111/j.1746-1561.2011.00663.x · Cited by 132
Representative Literature Reviews Using Constrained Snowball Sampling and Citation Network Analysis
Lecy, J. D., & Beatty, K. E. (2012) · doi:10.2139/ssrn.1992601 · Cited by 133
Network Exposure and Homicide Victimization in an African American Community
Papachristos, A. V., & Wildeman, C. (2014) · American Journal of Public Health · doi:10.2105/ajph.2013.301441 · Cited by 123
Urban Street Networks, a Comparative Analysis of Ten European Cities
Strano, E., Viana, M., da Fontoura Costa, L., Cardillo, A., Porta, S., & Latora, V. (2013) · Environment and Planning B: Planning and Design · doi:10.1068/b38216 · Cited by 121
Social network diagnostics: A tool for monitoring group interventions
Gesell, S. B., Barkin, S. L., & Valente, T. W. (2013) · Implementation Science · doi:10.1186/1748-5908-8-116 · Cited by 120
The effect of social interaction on learning engagement in a social networking environment
Lu, J., & Churchill, D. (2014) · Interactive Learning Environments · doi:10.1080/10494820.2012.680966 · Cited by 117
Modelling of pathways and movement networks in archaeology: an overview of current approaches
Verhagen, P., Nuninger, L., & Groenhuijzen, M. R. (2019) · Computational Social Sciences · doi:10.1007/978-3-030-04576-0_11 · Cited by 117
Interdisciplinarity in the environmental sciences: barriers and frontiers
HICKS, C. C., FITZSIMMONS, C., & POLUNIN, N. V. C. (2010) · Environmental Conservation · doi:10.1017/s0376892910000822 · Cited by 109
Spontaneous emergence of modularity in cellular networks
Solé, R. V., & Valverde, S. (2008) · Journal of The Royal Society Interface · doi:10.1098/rsif.2007.1108 · Cited by 102
Asher, L., Collins, L. M., Ortiz-Pelaez, A., Drewe, J. A., Nicol, C. J., & Pfeiffer, D. U. (2009) · Journal of The Royal Society Interface · doi:10.1098/rsif.2009.0221 · Cited by 102
Multi-Domain Information Fusion for Insider Threat Detection
Eldardiry, H., Bart, E., Liu, J., Hanley, J., Price, B., & Brdiczka, O. (2013) · 2013 IEEE Security and Privacy Workshops · doi:10.1109/spw.2013.14 · Cited by 100
Disentangling the effects of social network density on electronic word-of-mouth (eWOM) intention
Sohn, D. (2009) · Journal of Computer-Mediated Communication · doi:10.1111/j.1083-6101.2009.01444.x · Cited by 98
New farmers and networks: How beginning farmers build social connections in France
MAILFERT, K. (2007) · Tijdschrift voor Economische en Sociale Geografie · doi:10.1111/j.1467-9663.2007.00373.x · Cited by 96
Exposure to news grows less fragmented with an increase in mobile access
Yang, T., Majó-Vázquez, S., Nielsen, R. K., & González-Bailón, S. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2006089117 · Cited by 95
“For undirected, simple networks Dt = 2Et Vt (Vt−1), where Et is the number of edges at a particular time t and Vt is the number of vertices or nodes at a particular time t (25).”
BackgroundInferring social structure from temporal data
Psorakis, I., Voelkl, B., Garroway, C. J., Radersma, R., Aplin, L. M., Crates, R. A., Culina, A., Farine, D. R., Firth, J. A., Hinde, C. A., et al. (2015) · Behavioral Ecology and Sociobiology · doi:10.1007/s00265-015-1906-0 · Cited by 95
“For each resulting network, we calculated four different network measures: mean degree centrality (Wasserman and Faust 1994), mean edge weight disparity (Barthelemy et al. 2005), mean betweenness centrality (of the unweighted graph, Freeman 1979) and mean clustering coefficient (Watts 1999).”
Differences in Social Network Structure and Support Among Women in Violent Relationships
Katerndahl, D., Burge, S., Ferrer, R., Becho, J., & Wood, R. (2013) · Journal of Interpersonal Violence · doi:10.1177/0886260512469103 · Cited by 94
Single-item Big Five ratings in a social network design
Denissen, J. J. A., Geenen, R., Selfhout, M., & van Aken, M. A. G. (2008) · European Journal of Personality · doi:10.1002/per.662 · Cited by 91
Networks and social cohesion in ancient Indian Ocean trade: geography, ethnicity, religion
Seland, E. H. (2013) · Journal of Global History · doi:10.1017/s1740022813000338 · Cited by 77
The ontogeny of scale-free syntax networks: phase transitions in early language acquisition
COROMINAS-MURTRA, B., VALVERDE, S., & SOLÉ, R. (2009) · Advances in Complex Systems · doi:10.1142/s0219525909002192 · Cited by 71
Falling behind: Lingering costs of the high school transition for youth friendships and grades
Felmlee, D., McMillan, C., Inara Rodis, P., & Osgood, D. W. (2018) · Sociology of Education · doi:10.1177/0038040718762136 · Cited by 66
Li, Z. (., Fang, X., & Sheng, O. R. L. (2018) · ACM Transactions on Management Information Systems · doi:10.1145/3131782 · Cited by 65
“…also evaluate link recommendation diversity by measuring the diversity of a social network after adding recommended links with classical network metrics such as clustering coefficient (Watts and Strogatz 1998), network diameter (Wasserman and Faust 1994), and number of structural holes (Burt 1992).”
BackgroundPredicting happiness: user interactions and sentiment analysis in an online travel forum
Neidhardt, J., Rümmele, N., & Werthner, H. (2017) · Information Technology & Tourism · doi:10.1007/s40558-017-0079-2 · Cited by 61
It Is Better to Receive Than to Give: Advice Network Effects on Job and Work-Unit Attachment
Zagenczyk, T. J., & Murrell, A. J. (2009) · Journal of Business and Psychology · doi:10.1007/s10869-009-9095-3 · Cited by 54
The effect of online social network characteristics on consumer purchasing intention of social deals
Park, M.-S., Shin, J.-K., & Ju, Y. (2014) · Global Economic Review · doi:10.1080/1226508x.2014.884047 · Cited by 48
Valente, T. W., Fujimoto, K., Palmer, P., & Tanjasiri, S. P. (2010) · American Journal of Public Health · doi:10.2105/ajph.2009.171116 · Cited by 47
Lantz, B., & Hutchison, R. (2015) · Journal of Research in Crime and Delinquency · doi:10.1177/0022427815576754 · Cited by 47
Grygiel, P., Humenny, G., & Rębisz, S. (2019) · Assessment · doi:10.1177/1073191116682298 · Cited by 44
Impact of repeated exposures on information spreading in social networks
Zhou, C., Zhao, Q., & Lu, W. (2015) · PLoS ONE · doi:10.1371/journal.pone.0140556 · Cited by 42
“Analogous to the definition of ego network [34], we define this “wheel-like” directed network as direct follower network.”
Chang, H. (2009) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21070 · Cited by 42
Himelboim, I., & Golan, G. J. (2023) · Journal of Interactive Advertising · doi:10.1080/15252019.2022.2139653 · Cited by 42
Reconciling long-term cultural diversity and short-term collective social behavior
Valori, L., Picciolo, F., Allansdottir, A., & Garlaschelli, D. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1109514109 · Cited by 40
Drinking, Socioemotional Functioning, and Academic Progress in Secondary School
Crosnoe, R., Benner, A. D., & Schneider, B. (2012) · Journal of Health and Social Behavior · doi:10.1177/0022146511433507 · Cited by 38
Deepfakes on Twitter: Which Actors Control Their Spread?
Pérez Dasilva, J., Meso Ayerdi, K., & Mendiguren Galdospin, T. (2021) · Media and Communication · doi:10.17645/mac.v9i1.3433 · Cited by 38
Bret, C., Sueur, C., Ngoubangoye, B., Verrier, D., Deneubourg, J.-L., & Petit, O. (2013) · PLoS ONE · doi:10.1371/journal.pone.0083015 · Cited by 37
Hrastinski, S. (2010) · Integrated Series in Information Systems · doi:10.1007/978-1-4419-6139-6_6 · Cited by 31
Keerthipriya, P., Nandini, S., & Vidya, T. N. C. (2021) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2021.616666 · Cited by 27
Ramanadhan, S., Minsky, S., Martinez-Dominguez, V., & Viswanath, K. (2017) · Translational Behavioral Medicine · doi:10.1007/s13142-017-0488-y · Cited by 26
Bess, K. D., Speer, P. W., & Perkins, D. D. (2012) · Health Education & Behavior · doi:10.1177/1090198111419656 · Cited by 24
Systematic examination of pre‐ and post‐retraction citations
Dinh, L., Sarol, J., Cheng, Y., Hsiao, T., Parulian, N., & Schneider, J. (2019) · Proceedings of the Association for Information Science and Technology · doi:10.1002/pra2.35 · Cited by 23
“Specifically, ego-network analysis [Wasserman and Faust, 1994] where the retracted paper is the ego, is useful to reveal the dynamics between”
MethodDarius, P. (2022) · Social Network Analysis and Mining · doi:10.1007/s13278-022-00958-w · Cited by 22
Kwon, K. H. (2019) · Journal of Interactive Advertising · doi:10.1080/15252019.2018.1561342 · Cited by 22
Convergent Evolutionary Paths in Biological and Technological Networks
Solé, R. V., Valverde, S., & Rodriguez-Caso, C. (2011) · Evolution: Education and Outreach · doi:10.1007/s12052-011-0346-1 · Cited by 20
Harvey, N. D., Daly, C., Clark, N., Ransford, E., Wallace, S., & Yon, L. (2018) · Animals · doi:10.3390/ani8080132 · Cited by 19
“Definitions of the terms used in the social network analysis based upon Coleing [29], Wasserman & Faust [35], and Wey et al.”
BackgroundMethodInfluentialBUILDING THE YOUTH MENTORING KNOWLEDGE BASE: PUBLISHING TRENDS AND COAUTHORSHIP NETWORKS
Blakeslee, J. E., & Keller, T. E. (2012) · Journal of Community Psychology · doi:10.1002/jcop.21494 · Cited by 17
Rosenkrantz, J. T., Aarts, H., Abee, T., Rolfe, M. D., Knudsen, G. M., Nielsen, M.-B., Thomsen, L. E., Zwietering, M. H., Olsen, J. E., & Pin, C. (2013) · BMC Microbiology · doi:10.1186/1471-2180-13-294 · Cited by 13
Institutional Approaches for Studying System-Oriented Networks
Taylor, C., & Nowell, B. (2024) · Systems · doi:10.3390/systems12050159 · Cited by 3
“Like the parable of the blind men and the elephant, network-level analysis and descriptions based on incomplete data can produce a distorted representation [13].”
BackgroundPOI VizNet: New QGIS Tool to construct Visibility Networks in Cities
Natapov, A., Dalyot, S., & Cohen, A. (2024) · ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences · doi:10.5194/isprs-annals-x-4-2024-239-2024 · Cited by 1
Classic Communication Theories in the Digital Realm: A Literature Review
Tasente, T. (2026) · Mediaciones Sociales · doi:10.5209/meso.104881
“Social Network Theory (SNT), emerging from sociological research on social relations and information flow (Barnes, 1954; Granovetter, 1973; Wasserman & Faust, 1994), conceptualizes communication as a system of nodes and ties, where nodes represent social actors (individuals, organizations, or…”
Metadata
- Authors
- Wasserman, S., & Faust, K.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- University of South Carolina (US)
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 1994-11-25
- OpenAlex
- W950821216
- Cited by
- 17,557
- References
- 0
- Citations by year
- 2026: 619 · 2025: 780 · 2024: 747 · 2023: 763 · 2022: 783 · 2021: 931 · 2020: 907 · 2019: 898 · 2018: 955 · 2017: 891 · 2016: 877 · 2015: 872 · 2014: 974 · 2013: 947 · 2012: 856
- FWCI
- 10.62
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Cambridge University Press eBooks (publishedVersion)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Social Sciences › Sociology and Political Science › Social Capital and Networks
- Social Sciences › Sociology and Political Science › Social Power and Status Dynamics
- Keywords
- social network analysis, network methods, network data analysis, social networks, behavioral research, marketing, industrial engineering
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
