- Browse/Search Program
Search
Program Calendar
Browse By Day
Browse By Time
Browse By Person
Browse By Session Type
- Navigation and Settings Menu
Personal Schedule
Sign In
- Participant Resources
Access for All
Exhibit Hall
Hotels
WiFi
- Information Menu
Search Tips
Annual Meeting App
Onsite Guide
The Geopolitics of Corruption Narratives on Wikipedia
Mon, August 11, 4:00 to 5:00pm, East Tower, Hyatt Regency Chicago, Floor: Ballroom Level/Gold, Grand Ballroom AAbstract
This study investigates the narrative bias within Wikipedia articles concerning the global discourse on corruption. Through a detailed quantitative analysis, this research focuses on how the so-called "corrupt third world" narrative is prevalent in articles about nations in the global south compared to their global north counterparts. Utilizing a dataset that includes mentions of corruption across various nation profiles on Wikipedia, correlated with scores from the Corruption Perceptions Index (CPI), this study provides insights into how corruption is contextualized differently across regions.
The research employs a Python script to scrape Wikipedia data, analyzing the frequency with which corruption is mentioned in the context of different countries. Statistical tests are conducted to examine the relationship between the CPI scores and the frequency of corruption mentions, assess the distribution of corruption narratives geographically, and explore the potential biases introduced by the predominantly Western authorship of Wikipedia articles. Findings suggest a significant regional bias: countries in the global south are more likely to be discussed in terms of corruption than those in the global north, a disparity that likely reflects and reinforces stereotypical narratives of governance and morality.
This study raises critical questions about the role of popular online platforms in shaping global perceptions of corruption. By revealing a marked bias in how corruption is portrayed, it challenges the neutrality of global knowledge repositories like Wikipedia. The implications of these findings are profound, suggesting that the narrative constructions around corruption on widely accessed platforms could influence international policy, economic decisions, and public perceptions worldwide. Future work will aim to deepen the understanding of these biases and explore methods to mitigate their effects in global informational resources.