TL;DR
This work develops a multiagent simulation of a popular social network, Reddit, and uses millions of posts from users on the platform to model content-sharing on the platform.
This work proposes a, to their knowledge, novel auction based method for feed construction where users bid for the attention of other users, and systematically considers producers, consumers, platform operators, and social welfare.
It is shown that a network is uniquely optimal for some informational environment if and only if the focal agent observes every predecessor, and that which network performs best depends critically on the informational environment.
Recommender systems shape which content reaches users, making it important to measure whether coordinated activity gains visibility beyond the accounts that initiate it. Existing robustness evaluations largely focus on static target-rank changes and do not capture how coordinated interactions, recommendation, and user...
This paper studies the benefit related to interactions among activated nodes and proposes a new problem named discount allocation for benefit maximization, where a few selected users are offered with discounts and hope that they promote this influence to their friends so as to maximize the benefit between all influence...
A large literature uses exogenous variation to estimate how assignment to classrooms or other groups shapes social networks. Yet most of these analyses remain dyadic, treating each link in isolation, even though ties often form through triadic closure, as a friend of a friend also becomes a friend. Using fine-grained d...
Cluster weight on advice (CWOA) is proposed, a novel “two-shot” algorithm to identify a more accurate subgroup in a single-prediction-problem context and consistently outperforms benchmarks, including the state-of-the-art metaprediction-based methods.
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