• Medientyp: E-Artikel
  • Titel: Corporate Network Centrality Score: Methodologies and Informativeness
  • Beteiligte: Debreceny, Roger S.; Rahman, Asheq; Wang, Tawei
  • Erschienen: American Accounting Association, 2017
  • Erschienen in: Journal of Information Systems, 31 (2017) 3, Seite 23-43
  • Sprache: Englisch
  • DOI: 10.2308/isys-51797
  • ISSN: 1558-7959; 0888-7985
  • Schlagwörter: Management of Technology and Innovation ; Information Systems and Management ; Human-Computer Interaction ; Accounting ; Information Systems ; Software ; Management Information Systems
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  • Beschreibung: <jats:title>ABSTRACT</jats:title><jats:p>This research proposes a Corporation Network Centrality Score (CNCS) that exploits the social network implicit in Twitter interactions that are relevant to capital markets. The CNCS is the eigenvector network centrality score for interactions about corporations. The CNCS provides a summary numeric metric that captures a wide range of market-relevant information about the corporation it represents. The study asserts that the CNCS will assist the monitoring of corporations by auditors, regulators, and other market participants. The research calculates the CNCS for Standard &amp; Poor's (S&amp;P) 1500 firms and then tests the robustness of the metric by regressing CNCS on a set of variables that are known to convey firm fundamentals information to the capital markets. The study finds that CNCS is strongly associated with firm-led disclosures, market-based firm characteristics, and accounting-based firm fundamentals information.</jats:p><jats:p>JEL Classifications: M41.</jats:p>