SONIC: SOcial Network analysis with Influencers and Communities

Chen, C. Y.-H. , Härdle, W. K. and Klochkov, Y. (2021) SONIC: SOcial Network analysis with Influencers and Communities. Journal of Econometrics, (doi: 10.1016/j.jeconom.2021.02.008) (Early Online Publication)

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Abstract

The integration of social media characteristics into an econometric framework requires modeling a high dimensional dynamic network with dimensions of parameter typically much larger than the number of observations. To cope with this problem, we introduce SONIC, a new high-dimensional network model that assumes that (1) only few influencers drive the network dynamics; (2) the community structure of the network is characterized by homogeneity of response to specific influencers, implying their underlying similarity. An estimation procedure is proposed based on a greedy algorithm and LASSO regularization. Through theoretical study and simulations, we show that the matrix parameter can be estimated even when sample size is smaller than the size of the network. Using a novel dataset retrieved from one of leading social media platforms — StockTwits and quantifying their opinions via natural language processing, we model the opinions network dynamics among a select group of users and further detect the latent communities. With a sparsity regularization, we can identify important nodes in the network.

Item Type:Articles
Additional Information:Grants-DFG, Germany IRTG 1792, CAS, Czech Republic: XDA 23020303, and COST Action CA19130 gratefully acknowledged.
Status:Early Online Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Chen, Professor Cathy Yi-Hsuan
Authors: Chen, C. Y.-H., Härdle, W. K., and Klochkov, Y.
College/School:College of Social Sciences > Adam Smith Business School > Accounting and Finance
Journal Name:Journal of Econometrics
Publisher:Elsevier
ISSN:0304-4076
ISSN (Online):1872-6895
Published Online:12 April 2021
Copyright Holders:Copyright © 2021 The Author(s)
First Published:First published in Journal of Econometrics 2021
Publisher Policy:Reproduced under a Creative Commons license

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