SOCIOL 208A Reading Schedule (Fall 2024)
Week 1, October 2: Basic SNA Concepts
Readings
Prell, C. & Schaefer, D. R. (2023). Introducing Social Network Analysis. In J. McLevey, J. Scott, P. J. Carrington (Eds.) The SAGE Handbook of Social Network Analysis. Sage Publications. link
Light, R. & Moody, J. (2021). Network Basics: Points, Lines, and Positions. In R. Light, and J. Moody (Eds.) The Oxford Handbook of Social Networks Oxford University Press. link
Harary, F. & Norman., R. Z. (1953). Graph Theory as a Mathematical Model in Social Science. Research Center for Group Dynamics, University of Michigan. link
Other Material
Week 2, October 9: Centrality
Readings
Martin G. Everett & Steve P. Borgatti (2023). “Centrality.” In J. McLevey, J. Scott, P. J. Carrington (Eds.) The SAGE Handbook of Social Network Analysis. Sage Publications. link
Freeman, L. C. (1978). Centrality in Social Networks Conceptual Clarification. Social Networks, 1(3), 215-239. pdf
Koschützki, D., Lehmann, K.A., Peeters, L., Richter, S., Tenfelde-Podehl, D., Zlotowski, O. (2005). Centrality Indices. In: Brandes, U., Erlebach, T. (eds) Network Analysis. Lecture Notes in Computer Science, vol 3418. Springer, Berlin, Heidelberg (secs. 3.2, 3.3, and 3.4). link
Neal, Z. P. (2014). A network perspective on the processes of empowered organizations. American Journal of Community Psychology, 53, 407-418. https://doi.org/10.1007/s10464-013-9623-1
Agneessens, F., Borgatti, S. P., & Everett, M. G. (2017). Geodesic based centrality: Unifying the local and the global. Social Networks, 49, 12-26. link
Explainers
Other Material & Further Reading
Borgatti, S. P., & Everett, M. G. (2006). A graph-theoretic perspective on centrality. Social Networks, 28(4), 466-484. link
Brandes, U., Borgatti, S. P., & Freeman, L. C. (2016). Maintaining the duality of closeness and betweenness centrality. Social networks, 44, 153-159. link
Rossman, G., Esparza, N., & Bonacich, P. (2010). I’d Like To Thank The Academy, Team Spillovers, and Network Centrality. American Sociological Review, 75(1), 31-51. link
Koschützki, D., Lehmann, K.A., Tenfelde-Podehl, D., Zlotowski, O. (2005). Advanced Centrality Concepts. In: Brandes, U., Erlebach, T. (eds) Network Analysis. Lecture Notes in Computer Science, vol 3418. Springer, Berlin, Heidelberg. link
Comprehensive list of centrality measures with formulas and software
Week 3, October 16: Status and Prestige
Lizardo, O. (n.d.) Status link
Franceschet, M. (2011). PageRank: standing on the shoulders of giants. Communications of the ACM, 54(6), 92-101. link
Martin, J. L. & Murphy, J. P. (2021). Networks, Status, and Inequality. In R. Light, and J. Moody (Eds.) The Oxford Handbook of Social Networks Oxford University Press. link
Koschützki, D., Lehmann, K.A., Peeters, L., Richter, S., Tenfelde-Podehl, D., Zlotowski, O. (2005). Centrality Indices. In: Brandes, U., Erlebach, T. (eds) Network Analysis. Lecture Notes in Computer Science, vol 3418. Springer, Berlin, Heidelberg (sec. 3.9). link
Further (Mathy) Reading
Vigna, S. (2016). Spectral ranking. Network Science, 4(4), 433-445. pdf
Baltz, A., Kliemann, L. (2005). Spectral Analysis. In: Brandes, U., Erlebach, T. (eds) Network Analysis. Lecture Notes in Computer Science, vol 3418. Springer, Berlin, Heidelberg. link
Bonacich, P. (1972). Factoring and Weighting Approaches to Status Scores and Clique Identification. Journal of Mathematical Sociology, 2(1), 113-120. pdf
Katz, L. (1953). A New Status Index Derived from Sociometric Analysis. Psychometrika, 18(1), 39-43. pdf
Week 4, October 23:
No Class (Traveling)
Week 5, October 30: Similarity, Roles, and Positions
Readings
Burt, R. S. (1976). Positions in networks. Social Forces, 55(1), 93-122. link
Breiger, R. L., Boorman, S. A., & Arabie, P. (1975). An algorithm for clustering relational data with applications to social network analysis and comparison with multidimensional scaling. Journal of Mathematical Psychology, 12(3), 328-383. link
Lü, L., Jin, C. H., & Zhou, T. (2009). Similarity index based on local paths for link prediction of complex networks. Physical Review E—Statistical, Nonlinear, and Soft Matter Physics, 80(4), 046122. link
Jeh, G., & Widom, J. (2002). Simrank: a measure of structural-context similarity. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 538-543). link
Leicht, E. A., Holme, P., & Newman, M. E. (2006). Vertex similarity in networks. Physical Review E—Statistical, Nonlinear, and Soft Matter Physics, 73(2), 026120. link
Further Reading
Fouss, F., Pirotte, A., Renders, J. M., & Saerens, M. (2007). Random-walk computation of similarities between nodes of a graph with application to collaborative recommendation. IEEE Transactions on knowledge and data engineering, 19(3), 355-369. link
Kovács, B. (2010). A generalized model of relational similarity. Social Networks, 32(3), 197-211. link
Liben-Nowell, D., & Kleinberg, J. (2003). The link prediction problem for social networks. In Proceedings of the Twelfth Annual ACM International Conference on Information and Knowledge Management (CIKM’03) (pp. 556-559). link to longer paper
Lü, L., & Zhou, T. (2011). Link prediction in complex networks: A survey. Physica A: statistical mechanics and its applications, 390(6), 1150-1170. link
Cheat Sheet:
- Chroł, B & Bojanowski, M. (2018). Proximity-based Methods for Link Prediction. https://cran.r-project.org/web/packages/linkprediction/vignettes/proxfun.html
Week 6, November 6: Subgroups and Communities
Readings
Moody, J., & Mucha, P. J. (2023). Structural Cohesion and Cohesive Groups. In J. McLevey, J. Scott, P. J. Carrington (Eds.) The SAGE Handbook of Social Network Analysis. Sage Publications. link
Shai, S., Stanley, N., Granell, C., Taylor, D. & Mucha, P. J. (2021). Case Studies in Network Community Detection. In R. Light, and J. Moody (Eds.) The Oxford Handbook of Social Networks Oxford University Press. link
Newman, M. E. (2018). Community Structure. In Networks, 2nd Edition. Oxford, Online Edition, Oxford Academic. link
Fortunato, S. (2010). Community Detection in Graphs. Physics Reports, 486(3-5), 75-174. link
Further Reading
Newman, M. E. (2006). Modularity and Community Structure in Networks. Proceedings of the National Academy of Sciences, 103(23), 8577-8582. link
Clauset, A., Newman, M. E., & Moore, C. (2004). Finding community structure in very large networks. Physical Review E—Statistical, Nonlinear, and Soft Matter Physics, 70(6), 066111. link
Newman, M. E., & Girvan, M. (2003). Mixing patterns and community structure in networks. In Statistical mechanics of complex networks (pp. 66-87). Berlin, Heidelberg: Springer Berlin Heidelberg.
Newman, M. E. (2003). Mixing Patterns in Networks. Physical review E 67(2), 026126. link
Girvan, M., & Newman, M. E. (2002). Community Structure in Social and Biological Networks. Proceedings of the National academy of Sciences, 99(12), 7821-7826. link
Newman, M. E., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical review E, 69(2), 026113. link
Leicht, E. A., and Newman, M. E. (2008). Community Structure in Directed Networks. Physical Review Letters 100, 118703. link
Week 7, November 13: Analyzing Two-Mode Networks
Readings
Breiger, R. L. (1974). The Duality of Persons and Groups. Social Forces, 53(2), 181–190. link
Borgatti, S. P., & Everett, M. G. (1997). Network Analysis of 2-Mode Data. Social Networks, 19(3), 243-269. pdf
Everett, M. G., & Borgatti, S. P. (2013). The Dual-Projection Approach for Two-Mode Networks. Social Networks, 35(2), 204-210. link
Neal, Z. (2014). The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks, 39, 84-97. link
Further Reading
- Borgatti, S., & Halgin, D. (2014). Analyzing affiliation networks. In The SAGE Handbook of Social Network Analysis, First Edition (pp. 417-433), SAGE Publications Ltd. link
Other Material
Murphy, Phil, and Brendan Knapp. (2018). Bipartite/two-mode networks in igraph. RPubs https://rpubs.com/pjmurphy/317838
Domagalski, R., Neal, Z. P., & Sagan, B. (2021). Backbone: An R package for extracting the backbone of bipartite projections. Plos one, 16(1), e0244363. link
Neal, Z. P. (2022). backbone: An R package to extract network backbones. PloS one, 17(5), e0269137. link
Week 8, November 20: Ego Networks
Readings
- Smith, J. A. (2021). The Continued Relevance of Ego Network Data. In R. Light, and J. Moody (Eds.) The Oxford Handbook of Social Networks Oxford University Press. link
Week 9, November 27: Statistical Models of Network Structure
Readings
- Lusher D., Wang, P., Brennecke, J., Brailly J., Faye, M., Gallagher, C. (2021). Advances in Exponential Random Graph Models. In R. Light, and J. Moody (Eds.) The Oxford Handbook of Social Networks Oxford University Press. link
Week 10, December 4: Dynamic Networks and Relational Events
- TBA