APPLICATION OF MAXIMUM LIKELIHOOD METHOD FOR DIVIDING COMMUNITIES INTO THREE IN ECONOMICS
Keywords:
Maximum Likelihood Estimation, Social Networks, Economic Classifications, Market Segmentation, Gaussian Mixture Model, Probabilistic Model, User Classification, Economic Communities, Network Graph, Optimization Process, Community Membership.Abstract
This informative article explores the novel application of the Maximum Likelihood Estimation (MLE) method in the context of social networks from an economic perspective. It discusses the problem of classifying users of a social network into three distinct economic groups. It explains how MLE facilitates the identification of these groups by maximizing the likelihood of the observed data given certain parameters. By iterating and modifying group assignments and parameter estimates, MLE effectively segments markets and facilitates detailed investigations and targeted interventions. The article provides a practical problem and solution approach with numerical examples furthering the understanding of MLE's application in economic community segmentation.
References
Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer.
Dempster, A., Laird, N., & Rubin, D. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society: Series B (Methodological), 39 (1), 1-38.
Easley, D., & Kleinberg, J. (2010). Networks, Crowds, and Markets: Reasoning About a Highly Connected World. Cambridge University Press.
Fortunato, S. (2010). Community detection in graphs. Physics Reports, 486 (3-5), 75-174.
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT press.
Hastie, T., Tibshirani, R., & Friedman, J. (2009). Unsupervised Learning. The Elements of Statistical Learning. Springer, 485-585.
Newman, M. (2004). Detecting community structure in networks. The European Physical Journal B - Condensed Matter, 38 (2), 321–330.
Wasserman, S., & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press.
