Distinctiveness Centrality Compared to Beta and Gamma Centrality in Social Network Analysis
Distinctiveness centrality, while exhibiting some correlations with Beta and Gamma centralities under specific conditions, offers a distinct approach to measuring node importance in social networks, particularly when considering varying alpha values, network topologies, and weighted versus unweighted edges.
온라인 커뮤니티에서의 정보 확산: 인플루언서의 리포스트와 위신 편향 현상 분석
인플루언서는 단순히 많은 팔로워에게 정보를 전달하는 것을 넘어, 자신의 리포스트를 통해 다른 사용자의 정보 공유 행동을 유발하고, 이는 온라인에서 위신 편향 현상을 강화하며 정보 확산에 큰 영향을 미친다.
Modeling Social Influence and Network Interference in Psychological Research
Social network analysis can be used to model how individuals' beliefs, attitudes, and behaviors are influenced by their social connections, and how this social influence can interfere with experimental interventions.
Adaptive Social Learning Enables Discovery of Personalized Truths in Community-Structured Networks
The adaptive social learning strategy allows each community in a network to discover its own underlying truth, in contrast to traditional social learning which forces the entire network to converge to a common solution.
Emergent Group Dynamics in Wikipedia Editing: Insights from Analyzing Causal Patterns in User Interactions
The study reveals an emergent coherence in the sizes of transient groups that form to edit Wikipedia page content, with two key group sizes - around N=8 for maximum contention, and around N=4 as a regular team size. These findings align with previous predictions about social group sizes and have implications for understanding the self-organizing properties of online communities.
Open-source Software for Estimating Autologistic Actor Attribute Models (ALAAMs) for Social Influence
The autologistic actor attribute model (ALAAM) is a model for estimating parameters related to social influence or contagion processes in social networks. This work introduces ALAAMEE, open-source Python software for estimating, simulating, and evaluating ALAAM models.
Maximizing the Market Share of a New Product in a Competitive Environment through Targeted Community Formation
By strategically forming a community of targeted users and leveraging their influence, a new product can establish a positive market share even in a market dominated by an existing product.
Simulating Relational Event Histories to Assess Goodness-of-Fit and Develop Theories
Relational event simulations can be used to assess the goodness-of-fit of relational event models and to develop and test social theories about interaction dynamics in social networks.
Optimizing Multiplex Influence Maximization in Social Networks through Graph Bayesian Optimization
The core message of this paper is to introduce the Multiplex Influence Maximization (Multi-IM) problem, which aims to maximize the influence spread of multiple interconnected information items in a social network, and to propose a Graph Bayesian Optimization framework (GBIM) to effectively solve this problem.
RA-ICM: A Novel Independent Cascade Model Incorporating User Relationships and Attitudes
User relationships and attitudes significantly impact information propagation in social networks, necessitating a new model for accurate predictions.
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