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 301–400 of 1,053
Patterns of Link Reciprocity in Directed Networks
Garlaschelli, D., & Loffredo, M. I. (2004) · Physical Review Letters · doi:10.1103/physrevlett.93.268701 · Cited by 467
Evolution of Cooperation in Multiplex Networks
Gómez‐Gardeñes, J., Reinares, I., Arenas, À., & Florı́a, L. M. (2012) · Scientific Reports · doi:10.1038/srep00620 · Cited by 445
Statistical Models for Social Networks
Snijders, T. A. B. (2011) · Annual Review of Sociology · doi:10.1146/annurev.soc.012809.102709 · Cited by 482
Integrating Research on Interorganizational Networks and Ecosystems
Shipilov, A. V., & Gawer, A. (2019) · Academy of Management Annals · doi:10.5465/annals.2018.0121 · Cited by 513
Benedictis, L. D., & Tajoli, L. (2011) · World Economy · doi:10.1111/j.1467-9701.2011.01360.x · Cited by 486
Framing Interorganizational Network Change: A Network Inertia Perspective
Kim, T. Y., Oh, H., & Swaminathan, A. (2006) · Academy of Management Review · doi:10.5465/amr.2006.21318926 · Cited by 458
Attributed Social Network Embedding
Liao, L., He, X., Zhang, H., & Chua, T. (2018) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2018.2819980 · Cited by 457
“We conduct experiments on four public datasets, which are representative of two types of social networks—social friendship networks and academic citation networks [55].”
MethodThe Severity of Contract Enforcement in Interfirm Channel Relationships
Antia, K. D., & Frazier, G. L. (2001) · Journal of Marketing · doi:10.1509/jmkg.65.4.67.18385 · Cited by 455
Contractor, N., Wasserman, S. S., & Faust, K. (2006) · Academy of Management Review · doi:10.5465/amr.2006.21318925 · Cited by 450
Self-citationCarpenter, R. C. (2007) · International Studies Quarterly · doi:10.1111/j.1468-2478.2007.00441.x · Cited by 464
A Critical Review of Centrality Measures in Social Networks
Landherr, A., Friedl, B., & Heidemann, J. (2010) · Business & Information Systems Engineering · doi:10.1007/s12599-010-0127-3 · Cited by 484
Beyond Adoption: Development and Application of a Use-Diffusion Model
Shih, C., & Venkatesh, A. (2003) · Journal of Marketing · doi:10.1509/jmkg.68.1.59.24029 · Cited by 449
The Matthew effect in empirical data
Perc, M. (2014) · Journal of The Royal Society Interface · doi:10.1098/rsif.2014.0378 · Cited by 586
Impact of Co-Opetition on Firm Competitive Behavior: An Empirical Examination
Gnyawali, D. R., He, J., & Madhavan, R. (. (2006) · Journal of Management · doi:10.1177/0149206305284550 · Cited by 454
Community discovery using nonnegative matrix factorization
Wang, F., Li, T., Wang, X., et al. (2010) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-010-0181-y · Cited by 452
Discovering Social Networks from Event Logs
van der Aalst, W. M. P., Reijers, H. A., & Song, M. (2005) · Computer Supported Cooperative Work (CSCW) · doi:10.1007/s10606-005-9005-9 · Cited by 464
Tractable Models for Information Diffusion in Social Networks
Kimura, M., & Saito, K. (2006) · Lecture notes in computer science · doi:10.1007/11871637_27 · Cited by 453
Computing global structural balance in large-scale signed social networks
Facchetti, G., Iacono, G., & Altafini, C. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1109521108 · Cited by 433
The statistical analysis of data from small groups.
Kenny, D. A., Mannetti, L., Pierro, A., Livi, S., & Kashy, D. A. (2002) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.83.1.126 · Cited by 470
A framework for community identification in dynamic social networks
Tantipathananandh, C., Berger-Wolf, T. Y., & Kempe, D. (2007) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/1281192.1281269 · Cited by 449
TRIADS IN SUPPLY NETWORKS: THEORIZING BUYER–SUPPLIER–SUPPLIER RELATIONSHIPS
Choi, T. Y., & Wu, Z. (2008) · Journal of Supply Chain Management · doi:10.1111/j.1745-493x.2009.03151.x · Cited by 456
Designs for Collective Cognitive Responsibility in Knowledge-Building Communities
Zhang, J., Scardamalia, M., Reeve, R., & Messina, R. (2009) · Journal of the Learning Sciences · doi:10.1080/10508400802581676 · Cited by 472
Hara, N., Solomon, P. J., Kim, S., & Sonnenwald, D. H. (2003) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.10291 · Cited by 458
Gatekeepers of Knowledgewithin Industrial Districts: Who They Are, How They Interact
Morrison, A. (2008) · Regional Studies · doi:10.1080/00343400701654178 · Cited by 454
Orchestration Processes in Network-Centric Innovation: Evidence From the Field.
Nambisan, S., & Sawhney, M. (2011) · Academy of Management Perspectives · doi:10.5465/amp.2011.63886529 · Cited by 441
Leonardi, P. M. (2013) · MIS Quarterly · doi:10.25300/misq/2013/37.3.04 · Cited by 444
“If the density is equal to 1, then all dyads are mutual (Wasserman and Faust 1994, p. 129).”
BackgroundLin, Z. “., Yang, H., & Demirkan, I. (2007) · Management Science · doi:10.1287/mnsc.1070.0712 · Cited by 479
Tilly, C. (2005) · Cambridge University Press eBooks · doi:10.1017/cbo9780511618185 · Cited by 448
Avoiding Complexity Catastrophe in Coevolutionary Pockets: Strategies for Rugged Landscapes
McKelvey, B. (1999) · Organization Science · doi:10.1287/orsc.10.3.294 · Cited by 433
The Corner and the Crew: The Influence of Geography and Social Networks on Gang Violence
Papachristos, A. V., Hureau, D. M., & Braga, A. A. (2013) · American Sociological Review · doi:10.1177/0003122413486800 · Cited by 427
Organizational Social Network Research:Core Ideas and Key Debates
Kilduff, M. J., & Brass, D. J. (2010) · Academy of Management Annals · doi:10.1080/19416520.2010.494827 · Cited by 802
Truss decomposition in massive networks
Wang, J., & Cheng, J. S.-C. (2012) · Proceedings of the VLDB Endowment · doi:10.14778/2311906.2311909 · Cited by 431
Fang, R., Landis, B. D., Zhang, Z., Anderson, M. H., Shaw, J. D., & Kilduff, M. J. (2015) · Organization Science · doi:10.1287/orsc.2015.0972 · Cited by 451
“Indegree centrality indicates an individual’s level of activity (Freeman 1979), popularity (Wasserman and Faust 1994), or prominence (Knoke and Burt 1983) and is widely relevant in organizational research (e.g., Burkhardt and Brass 1990, Kilduff and Krackhardt 1994, Klein et al. 2004).”
BackgroundThe Peer Context of Adolescent Substance Use: Findings from Social Network Analysis
Ennett, S. T., Bauman, K. E., Hussong, A. M., Faris, R., Foshee, V. A., Cai, L., & DuRant, R. H. (2006) · Journal of Research on Adolescence · doi:10.1111/j.1532-7795.2006.00127.x · Cited by 443
Direct and indirect effects of third-party relationships on interpersonal trust.
Ferrin, D. L., Dirks, K. T., & Shah, P. P. (2006) · Journal of Applied Psychology · doi:10.1037/0021-9010.91.4.870 · Cited by 447
Hota, P. K., Subramanian, B., & Narayanamurthy, G. (2019) · Journal of Business Ethics · doi:10.1007/s10551-019-04129-4 · Cited by 476
PeerSoN: P2P social networking
Buchegger, S., Schiöberg, D., Vu, L., et al. (2009) · doi:10.1145/1578002.1578010 · Cited by 426
The Organization of Local and Distant Functional Connectivity in the Human Brain
Sepulcre, J., Liu, H., Talukdar, T., Martincorena, I., Yeo, B. T. T., & Buckner, R. L. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000808 · Cited by 428
The evolution of the world trade web: a weighted-network analysis
Fagiolo, G., Reyes, J. A., & Schiavo, S. (2009) · Journal of Evolutionary Economics · doi:10.1007/s00191-009-0160-x · Cited by 441
A brief survey on anonymization techniques for privacy preserving publishing of social network data
Zhou, B., Pei, J., & Luk, W.-S. (2008) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1540276.1540279 · Cited by 435
Street Centrality and Densities of Retail and Services in Bologna, Italy
Porta, S., Strano, E., Iacoviello, V., Messora, R., Latora, V., Cardillo, A., Wang, F., & Scellato, S. (2008) · Environment and Planning B Planning and Design · doi:10.1068/b34098 · Cited by 436
Twenty years of social capital and health research: a glossary
Moore, S., & Kawachi, I. I. (2017) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2016-208313 · Cited by 424
TAKING STOCK OF NETWORKS AND ORGANIZATIONS: A MULTILEVEL PERSPECTIVE.
Brass, D. J., Galaskiewicz, J. J., Greve, H. R., & Tsai, W. (2004) · Academy of Management Journal · doi:10.2307/20159624 · Cited by 2,611
When Competence Is Irrelevant: The Role of Interpersonal Affect in Task-Related Ties
Casciaro, T., & Lobo, M. S. (2008) · Administrative Science Quarterly · doi:10.2189/asqu.53.4.655 · Cited by 432
Boldi, P., & Vigna, S. (2014) · Internet Mathematics · doi:10.1080/15427951.2013.865686 · Cited by 478
“In recent years, there has been an ever-increasing research activity in the study of real-world complex networks [63] (the world-wide web, the autonomous-systems graph within the Internet, coauthorship graphs, phone-call graphs, email graphs and biological networks, to cite but a few).”
BackgroundSocial network analysis: An overview
Tabassum, S., Pereira, F. S. F., Fernandes, S., & Gama, J. (2018) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1256 · Cited by 581
Globalization Pressures and the State: The Worldwide Spread of Central Bank Independence
Polillo, S., & Guillén, M. F. (2005) · American Journal of Sociology · doi:10.1086/428685 · Cited by 412
Kagdi, H., Collard, M. L., & Maletic, J. I. (2007) · Journal of Software Maintenance and Evolution Research and Practice · doi:10.1002/smr.344 · Cited by 415
Organizing Rebellion: Rethinking High-Risk Mobilization and Social Networks in War
PARKINSON, S. E. (2013) · American Political Science Review · doi:10.1017/s0003055413000208 · Cited by 412
Algorithms for estimating relative importance in networks
White, S., & Smyth, P. (2003) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/956750.956782 · Cited by 418
Digital Business Strategy and Value Creation: Framing the Dynamic Cycle of Control Points
Pagani, M. (2013) · MIS Q. · doi:10.25300/misq/2013/37.2.13 · Cited by 395
Patterns and dynamics of users' behavior and interaction: Network analysis of an online community
Panzarasa, P., Opsahl, T., & Carley, K. M. (2009) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21015 · Cited by 438
Westphal, J. D., & Bednar, M. K. (2005) · Administrative Science Quarterly · doi:10.2189/asqu.2005.50.2.262 · Cited by 404
Lin, Y., Chi, Y., Shenghuo Zhu, B., Sundaram, H., & Tseng, B. L. (2008) · International World Wide Web Conference (WWW) · doi:10.1145/1367497.1367590 · Cited by 408
Towards Pervasive Augmented Reality: Context-Awareness in Augmented Reality
Grubert, J., Langlotz, T., Zollmann, S., & Regenbrecht, H. T. (2016) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2016.2543720 · Cited by 412
Team Boundary Spanning: A Multilevel Review of Past Research and Proposals for the Future
Marrone, J. A. (2010) · Journal of Management · doi:10.1177/0149206309353945 · Cited by 407
IT to Support Knowledge Sharing in Communities, towards a Social Capital Analysis
Huysman, M., & Wulf, V. (2005) · Journal of Information Technology · doi:10.1057/palgrave.jit.2000053 · Cited by 406
Social network analysis: developments, advances, and prospects
Scott, J. P. (2010) · Social Network Analysis and Mining · doi:10.1007/s13278-010-0012-6 · Cited by 403
Advancing the Science of Community-Level Interventions
Trickett, E. J., Beehler, S., Deutsch, C., Green, L. W., Hawe, P., McLeroy, K. R., Miller, R. L., Rapkin, B. D., Schensul, J. J., Schulz, A. J., et al. (2011) · American Journal of Public Health · doi:10.2105/ajph.2010.300113 · Cited by 404
Fletcher, R., & Nielsen, R. K. (2017) · Journal of Communication · doi:10.1111/jcom.12315 · Cited by 433
“Established techniques from the field of social network analysis (see e.g. Wasserman & Faust, 1994) can then be used to construct a network based on these relations.”
MethodGraph theory and networks in Biology
Mason, O., & Verwoerd, M. (2007) · IET Systems Biology · doi:10.1049/iet-syb:20060038 · Cited by 410
Network Theory and Small Groups
Katz, N. R., Lazer, D. M. J., Arrow, H., & Contractor, N. (2004) · Small Group Research · doi:10.1177/1046496404264941 · Cited by 423
Infection in Social Networks: Using Network Analysis to Identify High-Risk Individuals
Christley, R., Pinchbeck, G. L., Bowers, R., Clancy, D., French, N. P., Bennett, R., & Turner, J. (2005) · American Journal of Epidemiology · doi:10.1093/aje/kwi308 · Cited by 390
Do I Follow My Friends or the Crowd? Information Cascades in Online Movie Ratings
Lee, Y.-J., Hosanagar, K., & Tan, Y. (2015) · Management Science · doi:10.1287/mnsc.2014.2082 · Cited by 377
Morel, B., & Ramanujam, R. (1999) · Organization Science · doi:10.1287/orsc.10.3.278 · Cited by 400
AN EMERGENT THEORY OF STRUCTURE AND OUTCOMES IN SMALL-FIRM STRATEGIC MANUFACTURING NETWORKS.
Human, S. E., & Provan, K. G. (1997) · Academy of Management Journal · doi:10.5465/256887 · Cited by 432
Community Mining from Signed Social Networks
Yang, B. X., Cheung, W. K., & Liu, J. (2007) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2007.1061 · Cited by 388
Epistemic Network Analysis: A Prototype for 21st-Century Assessment of Learning
Shaffer, D. W., Hatfield, D., Svarovsky, G., Nash, P., Nulty, A., Bagley, E., Frank, K. A., Rupp, A. A., & Mislevy, R. J. (2009) · International Journal of Learning and Media · doi:10.1162/ijlm.2009.0013 · Cited by 394
Schmidt, J. E., Kent, A., Brisson, V. L., & Gaudin, A. (2019) · Microbiome · doi:10.1186/s40168-019-0756-9 · Cited by 331
Visser, P. S., & Mirabile, R. R. (2004) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.87.6.779 · Cited by 380
Discretion Within Constraint: Homophily and Structure in a Formal Organization
Kleinbaum, A. M., Stuart, T. E., & Tushman, M. L. (2013) · Organization Science · doi:10.1287/orsc.1120.0804 · Cited by 370
Vanhaverbeke, W. P. M., Duysters, G. M., & Noorderhaven, N. (2002) · Organization Science · doi:10.1287/orsc.13.6.714.496 · Cited by 388
Thinking Through Networks: A Review of Formal Network Methods in Archaeology
Brughmans, T. (2012) · Journal of Archaeological Method and Theory · doi:10.1007/s10816-012-9133-8 · Cited by 395
A Shapley Value-Based Approach to Discover Influential Nodes in Social Networks
Narayanam, R., & Narahari, Y. (2010) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2010.2052042 · Cited by 388
The institutional embeddedness of local inter-firm networks: a leverage for business creation
Johannisson, B., Ramírez‐Pasillas, M., & Karlsson, G. (2002) · Entrepreneurship and Regional Development · doi:10.1080/08985620210142020 · Cited by 388
Who Is the Best Connected Scientist?A Study of Scientific Coauthorship Networks
Newman, M. E. J. (2004) · Lecture notes in physics · doi:10.1007/978-3-540-44485-5_16 · Cited by 401
The Pressure of the Past: Network Imprinting in Intercorporate Communities
Marquis, C. (2003) · Administrative Science Quarterly · doi:10.2307/3556640 · Cited by 376
Dimensions of Leadership and Social Influence in Online Communities
Huffaker, D. A. (2010) · Human Communication Research · doi:10.1111/j.1468-2958.2010.01390.x · Cited by 404
Clusters, Connectivity and Catch-up: Bollywood and Bangalore in the Global Economy
Lorenzen, M., & Mudambi, R. (2012) · Journal of Economic Geography · doi:10.1093/jeg/lbs017 · Cited by 392
Applying centrality measures to impact analysis: A coauthorship network analysis
Yan, E., & Ding, Y. (2009) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21128 · Cited by 419
Narrative Networks: Patterns of Technology and Organization
Pentland, B. T., & Feldman, M. S. (2007) · Organization Science · doi:10.1287/orsc.1070.0283 · Cited by 370
The Structure of Founding Teams: Homophily, Strong Ties, and Isolation among U.S. Entrepreneurs
Ruef, M., Aldrich, H. E., & Carter, N. M. (2003) · American Sociological Review · doi:10.2307/1519766 · Cited by 1,249
Predictors and outcomes of networking intensity among unemployed job seekers.
Wanberg, C. R., Kanfer, R., & Banas, J. T. (2000) · Journal of Applied Psychology · doi:10.1037/0021-9010.85.4.491 · Cited by 389
Leveraging social media networks for classification
Tang, L., & Liu, H. (2011) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-010-0210-x · Cited by 360
Founder Centrality and Strategic Behavior in the Family-Owned Firm
Kelly, L., Athanassiou, N. A., & Crittenden, W. F. (2000) · Entrepreneurship Theory and Practice · doi:10.1177/104225870002500202 · Cited by 381
SHARED LEADERSHIP IN TEAMS: AN INVESTIGATION OF ANTECEDENT CONDITIONS AND PERFORMANCE.
CARSON, J. B., TESLUK, P. E., & MARRONE, J. A. (2007) · Academy of Management Journal · doi:10.2307/20159921 · Cited by 1,432
Finding Frequent Patterns in a Large Sparse Graph*
Kuramochi, M., & Karypis, G. (2005) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-005-0003-9 · Cited by 378
Cognitive divergence and shared mental models in software development project teams
Levesque, L. L., Wilson, J. M., & Wholey, D. R. (2001) · Journal of Organizational Behavior · doi:10.1002/job.87 · Cited by 367
Structural properties of planar graphs of urban street patterns
Cardillo, A., Scellato, S., Latora, V., & Porta, S. (2006) · Physical Review E · doi:10.1103/physreve.73.066107 · Cited by 370
New Frontiers in Network Theory Development
Parkhe, A., Wasserman, S. S., & Ralston, D. A. (2006) · Academy of Management Review · doi:10.5465/amr.2006.21318917 · Cited by 365
Self-citationRecommender Systems in Technology Enhanced Learning
Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H. G. K., & Koper, R. (2010) · Springer eBooks · doi:10.1007/978-0-387-85820-3_12 · Cited by 370
Dahlander, L., & McFarland, D. A. (2013) · Administrative Science Quarterly · doi:10.1177/0001839212474272 · Cited by 369
Distribution of Knowledge, Group Network Structure, and Group Performance
Rulke, D. L., & Galaskiewicz, J. (2000) · Management Science · doi:10.1287/mnsc.46.5.612.12052 · Cited by 364
Quantifying the Performance of Individual Players in a Team Activity
Duch, J., Waitzman, J. S., & Amaral, L. A. N. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010937 · Cited by 366
A network perspective on managing stakeholders for sustainable urban tourism
Timur, S., & Getz, D. (2008) · International Journal of Contemporary Hospitality Management · doi:10.1108/09596110810873543 · Cited by 393
The density of social networks and fertility decisions: Evidence from South Nyanza district, Kenya
Kohler, H., Behrman, J. R., & WATKINS, S. C. (2001) · Demography · doi:10.1353/dem.2001.0005 · Cited by 364
Conversations in the Blogosphere: An Analysis "From the Bottom Up"
Herring, S. C., Kouper, I., Paolillo, J. C., et al. (2005) · Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · doi:10.1109/hicss.2005.167 · Cited by 364
Leydesdorff, L., & Vaughan, L. Q. (2006) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.20335 · Cited by 363
Toward a basic framework for webometrics
Björneborn, L., & Ingwersen, P. (2004) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.20077 · Cited by 360
Where Do Creative Interactions Come From? The Role of Tie Content and Social Networks
Sosa, M. E. (2010) · Organization Science · doi:10.1287/orsc.1090.0519 · Cited by 357
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