Table 3 Results from applying the Newman-Girvan clustering algorithm to our abstraction hierarchy
Component name | Nodes |
|---|---|
Relationship | Adaption, coping, and interaction over time, locations (of the two individuals), racial income disparities, relationship |
Algorithms, policies, and norms | Algorithms, click through to user profile, community behaviors, community messaging, community policies, fairness constraint, optimization function |
Categorization | minimal group categories & filters, race-based categories & filters, search filters presented, user profile layout |
User cognition | dating history, mental model of offline dating, mental model of online dating, preferences, stereotypes |
User goals, constraints, and actions | communicate with potential partner, cultural expectations, effort required, find long term partner, increase interracial relationships, offline dating, personal desires and values, reduce racial income disparity and segregation, self present |
Platform goals and constraints | Data-driven insights, dating/matchmaking theories, effort reduction, find long-term partner, help people find a long-term partner, maximize profit, profit from data (wanted by advertisers) |