The empirical part of our research studied a social trading platform that today counts more than 20 million traders. Our random sample consisted of 28,000 active traders, which we analyzed over 38 weeks. On this platform, traders can “follow” or “copy” the actions of other users; if they opt to “copy,” then the decisions of the copied trader are automatically applied to the portfolio of the copier. For example, if Trader Alpha decides to copy Trader Beta and Trader Beta buys Stock X, that decision is automatically applied to trader Alpha, who will find Stock X in their investment portfolio. Clearly, the decision to copy a trader reflects the trust placed in that individual.
By analyzing the network structure and the behaviors of traders (such as the expression of positive sentiments in messages), we identified two main mechanisms that explain the accumulation of trust: social position and behavioral signals.
- Structural signals: An actor in a high-status position in the network, which coincides with being “followed” by actors who themselves have a very high number of followers on the platform, is perceived as more trustworthy. This effect derives from the association between status and competence: actors who count prestigious individuals (i.e., those with a very high number of followers) among their followers tend to be perceived as more competent, and therefore more trustworthy.
- Behavioral signals: The visible behaviors of actors, particularly the expression of positive sentiments in public messages, transmit signals of benevolence and good intentions. These signals not only directly influence the recipients of the interactions but also other network members who observe these exchanges.
- Combined effect: The combination of high status and positive behaviors has a synergistic effect on the accumulation of trust. A high-status trader who communicates positively accrues significantly more trust than a trader in a lower position or with less open, positive behaviors.
The term “prismatic trust” derives from the idea that, within a network, trust is not based solely on direct interactions but on signals that the network itself reflects like a prism. Just as a prism breaks down light into various colors, social networks break down and amplify different trust signals (structural and behavioral), making them visible to a much larger number of observers than bilateral interactions.
This prismatic view departs from traditional trust models, which focus on mechanisms based on direct exchange relationships or indirect signals through intermediate connections. The prismatic trust model introduces a new perspective, emphasizing how digital social networks, particularly those with high public visibility like social trading platforms, allow the generation of trust on a large scale, even among actors who are not directly connected.