This is to cordially invite you to the doctoral defense of
Manran Zhu
(Doctor of Philosophy in Network Science)
Dissertation Committee:
Federico Battiston (DNDS, chairperson, voting member)
János Kertész (DNDS, supervisor, non-voting member)
Rossano Schifanella (University of Turin, reviewer, voting member)
Milena Tsvetkova (London School of Economics, reviewer, voting member
ABSTRACT / With the rapid accumulation of online information, efficient web navigation has grown vital yet challenging. To create an easily navigable cyberspace catering to diverse demographics, understanding how people navigate differently is paramount. Previous research has discovered multiple patterns in how individuals navigate in the geographic, social, and information spaces, yet individual differences in navigation performance and strategies in the knowledge space has remained largely unexplored. To bridge the gap, we conduct an online experiment where participants played a navigation game on Wikipedia and completed questionnaires about their personal information. Our analysis shows that age negatively affects knowledge space navigation performance, while multilingualism enhances it. Under time pressure, participants' performance improves across trials and males outperform females, an effect not observed in games without time pressure. In our experiment, successful route-finding is usually not related to abilities of innovative exploration of routes. Utilizing a graph embedding trained on the English Wikipedia, our study identifies distinctive strategies that participants adopt: when the target is a famous person, participants typically use the geographical and occupational information of the target to navigate, reminiscent of hub-driven and proximity-driven approaches respectively. We discover that many participants playing the same game exhibit a "wisdom of the crowd" effect: The set of strategies provide a good estimate for the information landscape around the target indicating that the individual differences complement each other.
BIO / Manran's main research interest is to apply statistical physics method to study social phenomena. Her previous research topics include: quantum random walks on the embedded hypercube, modern approaches to thermodynamics, agent based modelling of opinion dynamics on networks, cost model on multi-layer transportation networks.