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Social network analysis in accounting information systems research

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  • Worrell, James
  • Wasko, Molly
  • Johnston, Allen

Abstract

This paper introduces social network analysis as an alternative research method for conducting accounting information systems related research. With advances in information and communication technologies, transaction data are being recorded in electronic form, resulting in a variety of research opportunities to examine dyadic interactions. A network consists of a set of nodes connected by ties. Social network research focuses on how outcomes are influenced not just by the attributes of the nodes (e.g. individuals), but also by the ties connecting nodes to each other. The nodes are typically conceptualized as actors, such as individuals, teams, or organizations. A unique network structure is created to reflect each different type of tie, such as trust, advice, collocation, or organizational affiliation. Social network analysis can be used for research examining individual, dyadic or network levels of analyses, and is a powerful tool for conducting multi-method research. Given the vast amounts of trace electronic data collected via accounting information systems, this paper reviews how social network analysis not only opens new research avenues for accounting information systems researchers, but identifies opportunities for the field of accounting information systems to inform social network research by identifying new network structures and dynamics leveraging transactional data.

Suggested Citation

  • Worrell, James & Wasko, Molly & Johnston, Allen, 2013. "Social network analysis in accounting information systems research," International Journal of Accounting Information Systems, Elsevier, vol. 14(2), pages 127-137.
    • Handle: RePEc:eee:ijoais:v:14:y:2013:i:2:p:127-137
    DOI: 10.1016/j.accinf.2011.06.002
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    References listed on IDEAS

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    3. Ahmad H. Juma’h & Yazan Alnsour, 2018. "Using Social Media Analytics: The Effect of President Trump’s Tweets On Companies’ Performance," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 17(1), pages 100-121, March.
    4. Charl de Villiers & Matteo La Torre & Vida Botes, 2022. "Accounting and social capital: A review and reflections on future research opportunities," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(4), pages 4485-4521, December.
    5. Gregory D. Saxton & Charlotte Ren & Chao Guo, 2021. "Responding to Diffused Stakeholders on Social Media: Connective Power and Firm Reactions to CSR-Related Twitter Messages," Journal of Business Ethics, Springer, vol. 172(2), pages 229-252, August.
    6. Gianni Onesti & Riccardo Palumbo, 2023. "Tone at the Top for Sustainable Corporate Governance to Prevent Fraud," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
    7. Slobodan Kacanski & Dean Lusher, 2017. "The Application of Social Network Analysis to Accounting and Auditing," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 7(3), pages 182-197, July.
    8. Saxton, Gregory D. & Guo, Chao, 2020. "Social media capital: Conceptualizing the nature, acquisition, and expenditure of social media-based organizational resources," International Journal of Accounting Information Systems, Elsevier, vol. 36(C).
    9. Giovanni Carnazza & Pierluigi Vellucci, 2022. "Network analysis and Eurozone trade imbalances," Papers 2209.09837, arXiv.org.
    10. So-Jin Yu & Jin-Sung Rha, 2021. "Research Trends in Accounting Fraud Using Network Analysis," Sustainability, MDPI, vol. 13(10), pages 1-26, May.
    11. Gray, Glen L. & Debreceny, Roger S., 2014. "A taxonomy to guide research on the application of data mining to fraud detection in financial statement audits," International Journal of Accounting Information Systems, Elsevier, vol. 15(4), pages 357-380.

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