The Social Construction of Online Fraud
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Yekta, Semire. 2019. The Social Construction of Online Fraud. Doctoral thesis, Goldsmiths, University of London [Thesis]
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Text (The Social Construction of Online Fraud)
SOC_thesis_YektaS_2019.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) | Preview |
Abstract or Description
This study critically examines how online retailers aim to differentiate between fraudulent and non-fraudulent customers by using digitally accessible data. Utilising social constructionism and actor-network theory as a theoretical framework, the study argues that online fraud is constructed through social practices as well as technological and organisational relations. This ongoing process involves several human and non-human actors embedded in heterogeneous networks, but the process is not neutral, and neither can the data used as the basis of fraud management be considered value-free. Big data has often been challenged as a neutral representation of reality, given that the collection and analysis thereof involve human biases, choices, selections and preferences. Consequently, the categories of risk assessment and manual fraud management practices represent these values.
However, from a manual fraud review perspective, automated fraud management systems gain an object-like status and often remain unchallenged, and the choices and selections behind these implementations go unnoticed. Categorisations and fraud scorings are pre-giving when manual reviewers enter the risk assessment process and can only operate within existing norms and structures. Manual reviewers take a similar approach and make decisions using additional data sources such as Google and personal and professional websites while imposing their own preferences, biases and understandings, or accepting, rejecting or negotiating alternative realities proposed by other reviewers. It is also crucial how manual reviewers are able to enrol and mobilise other actors to take action in line with their own interests.
The study shows that fraud assessment approaches create their own sense of normality and label those as suspicious or fraudulent who seem to deviate from the norm, thereby leading to the inclusion and exclusion of people. Furthermore, most fraud cases are not reported, which means that the vast majority remain unknown to the police, who then construct their own version of the crime.
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Item Type: |
Thesis (Doctoral) |
| Identification Number (DOI): |
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| Keywords: |
Online Fraud, Payment Fraud, E-Commerce Fraud, Cybercrime, Social Construction, Big Data |
| Departments, Centres and Research Units: |
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| Date: |
30 September 2019 |
| Item ID: |
27649 |
| Date Deposited: |
26 Nov 2019 11:03 |
| Last Modified: |
07 Sep 2022 17:15 |
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URI: |
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