Inward and Outward Network Influence Analysis

References

• Anselin, L. (1988), Spatial Econometrics: Methods and Models, Dordrecht: Kluwer Academic Press.
   Google Scholar
• Bamakan, S. M. H., Nurgaliev, I., and Qu, Q. (2019), “Opinion Leader Detection: A Methodological Review,” Expert Systems With Applications, 115, 200–222. DOI: 10.1016/j.eswa.2018.07.069.
   Web of Science ®Google Scholar
• Banerjee, A., Chandrasekhar, A. G., Duflo, E., and Jackson, M. O. (2013), “The Diffusion of Microfinance,”Science, 341, 1236498. DOI: 10.1126/science.1236498.
   PubMed Web of Science ®Google Scholar
• Banerjee, A., Chandrasekhar, A. G., Duflo, E., and Jackson, M. O. (2014), “Gossip: Identifying Central Individuals in a Social Network,” National Bureau of Economic Research, No. w20422.
   Google Scholar
• Bramoullé, Y., Djebbari, H., and Fortin, B. (2009), “Identification of Peer Effects Through Social Networks,” Journal of Econometrics, 150, 41–55. DOI: 10.1016/j.jeconom.2008.12.021.
   Web of Science ®Google Scholar
• Carrington, P. J., Scott, J., and Wasserman, S. (2005), Models and Methods in Social Network Analysis, Cambridge: Cambridge University Press.
   Google Scholar
• Catalini, C., and Tucker, C. (2017), “When Early Adopters Don’t Adopt,” Science, 357, 135–136. DOI: 10.1126/science.aal4476.
   PubMed Web of Science ®Google Scholar
• Dou, B., Parrella, M. L., and Yao, Q. (2016), “Generalized Yule–Walker Estimation for Spatio-Temporal Models With Unknown Diagonal Coefficients,” Journal of Econometrics, 194, 369–382.
   Web of Science ®Google Scholar
• Fan, J., and Li, R. (2001), “Variable Selection Via Nonconcave Penalized Likelihood and Its Oracle Properties,” Journal of the American Statistical Association, 96, 1348–1360. DOI: 10.1198/016214501753382273.
   Web of Science ®Google Scholar
• Gao, Z., Ma, Y., Wang, H., and Yao, Q. (2019), “Banded Spatio-Temporal Autoregressions,” Journal of Econometrics, 208, 211–230. DOI: 10.1016/j.jeconom.2018.09.012.
   Web of Science ®Google Scholar
• Gupta, A., and Robinson, P. M. (2015), “Inference on Higher-Order Spatial Autoregressive Models With Increasingly Many Parameters,” Journal of Econometrics, 186, 19–31. DOI: 10.1016/j.jeconom.2014.12.008.
   Web of Science ®Google Scholar
• Hastie, T., Tibshirani, R., and Friedman, J. (2009), The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd ed., New York: Springer.
   Google Scholar
• Katona, Z., Zubcsek, P. P., and Sarvary, M. (2011), “Network Effects and Personal Influences: The Diffusion of an Online Social Network,” Journal of Marketing Research, 48, 425–443. DOI: 10.1509/jmkr.48.3.425.
   Web of Science ®Google Scholar
• Kumar, V., and Reinartz, V. (2018), Customer Relationship Management: Concept, Strategy, and Tools, Berlin: Springer.
   Google Scholar
• Kwok, H. H. (2019), “Identification and Estimation of Linear Social Interaction Models,” Journal of Econometrics, 210, 434–458. DOI: 10.1016/j.jeconom.2018.07.010.
   Web of Science ®Google Scholar
• Lam, C., and Souza, P. (2019), “Estimation and Selection of Spatial Weight Matrix in a Spatial Lag Model,” Journal of Business & Economic Statistics, 1–41.
   Web of Science ®Google Scholar
• Lan, W., Fang, Z., Wang, H., and Tsai, C.-L. (2018), “Covariance Matrix Estimation Via Network Structure,” Journal of Business & Economic Statistics, 36, 359–369.
   Web of Science ®Google Scholar
• Lawyer, G. (2015), “Understanding the Influence of all Nodes in a Network,” Nature: Scientific Reports, 5, 8665.
   PubMed Web of Science ®Google Scholar
• Lee, L. F. (2004), “Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models,” Econometrica, 72, 1899–1925. DOI: 10.1111/j.1468-0262.2004.00558.x.
   Web of Science ®Google Scholar
• LeSage, J., and Pace, R. K. (2009), Introduction to Spatial Econometrics, New York: Chapman & Hall.
   Google Scholar
• Li, Y., Ma, S., Zhang, Y., and Huang, R. (2013), “An Improved Mix Framework for Opinion Leader Identification in Online Learning Communities,” Knowledge-Based Systems, 43, 43–51.
   Web of Science ®Google Scholar
• Liu, X. D., and Lee, L. F. (2010), “GMM Estimation of Social Interaction Models With Centrality,” Journal of Econometrics, 159, 99–115. DOI: 10.1016/j.jeconom.2010.04.009.
   Web of Science ®Google Scholar
• Ma, N., and Liu, Y. (2014), “SuperedgeRank Algorithm and Its Application in Identifying Opinion Leader of Online Public Opinion Supernetwork,” Expert Systems With Applications, 41, 1357–1368. DOI: 10.1016/j.eswa.2013.08.033.
   Web of Science ®Google Scholar
• Maggio, M. D., Franzoni, F., Kermani, A., and Sommavilla, C. (2019), “The Relevance of Broker Networks for Information Diffusion in the Stock Market,” Journal of Financial Economics, 134, 419–446. DOI: 10.1016/j.jfineco.2019.04.002.
   Web of Science ®Google Scholar
• Manski, C. F. (1993a), “Identification of Endogenous Social Effects: The Reflection Problem,” The Review of Economic Studies, 60, 531–542.
   Web of Science ®Google Scholar
• Manski, C. F. (1993b), “Identification Problems in the Social Sciences,” American Sociological Association, 23, 1–56.
   Google Scholar
• Mattila, M., Karjaluoto, H., and Pento, T. (2003), “Internet Banking Adoption Among Mature Customers: Early Majority or Laggards?” Journal of Services Marketing, 17, 514–528. DOI: 10.1108/08876040310486294.
   Google Scholar
• Ram, S., and Jung, H. S. (1994), “Innovativeness in Product Usage: A Comparison of Early Adopters and Early Majority,” Psychology & Marketing, 11, 57–67.
   Google Scholar
• Scott, J. (2013), Social Network Analysis, 3rd ed., London: Sage.
   Google Scholar
• Shi, P., and Tsai, C.-L. (2002). “Regression Model Selection–A Residual Likelihood Approach,” Journal of the Royal Statistical Society, Series B, 64, 237–252. DOI: 10.1111/1467-9868.00335.
   Google Scholar
• Storey, J. D., Taylor, J. E., and Siegmund, D. (2004), “Strong Control, Conservative Point Estimation and Simultaneous Conservative Consistency of False Discovery Rates: A Unified Approach,” Journal of the Royal Statistical Society, Series B, 66, 187–205. DOI: 10.1111/j.1467-9868.2004.00439.x.
   Google Scholar
• Tabassum, S., Pereira, F. S. F., Fernandes, S., and Gama, J. (2018), “Social Network Analysis: An Overview,” Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8, e1256.
   Web of Science ®Google Scholar
• Trusov, M., Bodapati, A., and Bucklin, R. (2010), “Determining Influential Users in Internet Social Networks,” Journal of Marketing Research, 47, 643–658. DOI: 10.1509/jmkr.47.4.643.
   Web of Science ®Google Scholar
• Valente, T. W. (2010), Social Networks and Health: Models, Methods, and Applications 1st Edition, Oxford University Press.
   Google Scholar
• Vuong, Q. H. (1989), “Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses,” Econometrica, 57, 307–333. DOI: 10.2307/1912557.
   Web of Science ®Google Scholar
• Wang, H., Li, R., and Tsai, C.-L. (2007). “Tuning Parameter Selectors for the Smoothly Clipped Absolute Deviation Method,” Biometrika, 94, 553–568. DOI: 10.1093/biomet/asm053.
   PubMed Web of Science ®Google Scholar
• Wolf, A., and Seebauer, S. (2014). “Technology Adoption of Electric Bicycles: A Survey Among Early Adopters,” Transportation Research Part A: Policy and Practice, 69, 196–211. DOI: 10.1016/j.tra.2014.08.007.
   Web of Science ®Google Scholar
• Yu, J., Robert, J., and Lee, L. (2008), “Quasi-Maximum Likelihood Estimators for Spatial Dynamic Panel Data With Fixed Effects When Both n and T Are Large,” Journal of Econometrics, 146, 118–134. DOI: 10.1016/j.jeconom.2008.08.002.
   Web of Science ®Google Scholar
• Zhang, Q., and Wang, H. (2011), “On BIC’s Selection Consistency for Discriminant Analysis,” Statistica Sinica, 21, 731–740. DOI: 10.5705/ss.2011.032a.
   Web of Science ®Google Scholar
• Zhang, X., and Yu, J. (2018), “Spatial Weights Matrix Selection and Model Averaging for Spatial Autoregressive Models,” Journal of Econometrics, 203, 1–18. DOI: 10.1016/j.jeconom.2017.05.021.
   Web of Science ®Google Scholar
• Zhang, X., Pan, R., Guan, G., Zhu, X., and Wang, H. (2020), “Logistic Regression With Network Data,” Statistica Sinica, 30, 673–693.
   Web of Science ®Google Scholar
• Zhou, J., Tu, Y., Chen, Y., and Wang, H. (2017), “Estimating Spatial Autocorrelation With Sampled Network Data,” Journal of Business & Economics Statistics, 35, 130–138.
   Web of Science ®Google Scholar
• Zhu, X., Chang, X., Li, R., and Wang, H. (2019), “Portal Nodes Screening for Large Scale Social Networks,” Journal of Econometrics, 209, 145–157. DOI: 10.1016/j.jeconom.2018.12.021.
   PubMed Web of Science ®Google Scholar
• Zhu, X., Pan, R., Li, G., Liu, Y., and Wang, H. (2017), “Network Vector Autoregression,” The Annals of Statistics, 45, 1096–1123. DOI: 10.1214/16-AOS1476.
   Web of Science ®Google Scholar
• Zou, T., Luo, R., Lan, W., and Tsai, C.-L. (2021), “Network Influence Analysis,” Statistica Sinica.
   Web of Science ®Google Scholar