Abstract
Many forms of cooperative relations in our society require mutual trust between parties. Trust is usually supported by legal institutions or personal relationships. However, some societal contexts lack institutionalized guarantees enforced by the legal system and long-standing personal relationships. This dissertation explores how people establish trust in uncertain situations where legal arrangements and personal relationships are not present. First, we map the conditions that lead social groups to develop social norms that help identify trustworthy individuals in uncertain social contexts. Then, we turn to online marketplaces for illegal trade as an intriguing context for the exploration of trust in adverse settings. We first find that market participants rely on both technological solutions and rich social interaction to identify trustworthy individuals and punish untrustworthy ones. We then demonstrate to what extent market participants’ other-regarding concerns aid in creating a knowledge base about reputations in the market, thereby supporting trust-building in an anonymous online contexts. We use text mining technique to understand how market participants communicate about others’ trustworthiness online. Additionally, we offer best practice advice for utilizing advanced methods for automatic text analysis in social sciences.
Original language | English |
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Qualification | Doctor of Philosophy |
Awarding Institution |
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Supervisors/Advisors |
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Award date | 19 Apr 2024 |
Place of Publication | Utrecht |
Publisher | |
Print ISBNs | 978-90-393-7653-9 |
DOIs | |
Publication status | Published - 19 Apr 2024 |
Keywords
- trust
- cooperation
- social norms
- signalling
- trustworthiness
- text analysis
- text mining
- large language models
- cryptomarkets
- communication