Belief-Augmented Social Network
To capture social interactions and bridge distant communities, our approach incorporates both existing and induced social information to construct a network that focuses on modeling users’ beliefs.

Our graph can be formally defined as follows: it comprises three sets of nodes, namely \mathcal{V}^{M} representing the news media messages, \mathcal{V}^{U} representing the users, and \mathcal{V}^{B} representing a fixed set of belief nodes. The graph consists of three types of edges: \mathcal{E}^{I} , \mathcal{E}^{F} , and \mathcal{E}^{B} . For each edge (u,m)\in\mathcal{E}^{I} , where u\in\mathcal{V}^{U} and m\in\mathcal{V}^{M} , it indicates that user u has interacted with the news media message m . For each edge (u_{1},u_{2})\in\mathcal{E}^{F} , where u_{1},u_{2}\in\mathcal{V}^{U} , it signifies that user u_{1} follows user u_{2} . Lastly, for each edge (u,b)\in\mathcal{E}^{B} , where u\in\mathcal{V}^{U} and b\in\mathcal{V}^{B} , it denotes that user u believes in the value represented by node b . An illustrative example sub-graph of the network is shown in Figure 3 .

Social Relation Network The first layer of our network consists of the user-user social network, where edges from User a to b indicate that User a follows User b . This network captures the interests of users and the relationships between users.

User-Media Interactions The second component of our network comprises news nodes and response edges indicating the users in the network have responded to these news nodes in the dataset. This feature offers two advantages. Firstly, it serves as a representation of users’ interests. Secondly, it facilitates the connection of users who are geographically distant in the network but might share interests in news topics, thus enabling the expansion of the set of potentially reliable neighbors for any user we would like to predict.

Belief-Centered Graph Lastly, we introduce belief nodes, composed of moral and human values (principles that guide behaviors) from the Latent Personas.

Moral Values :
Moral values are derived from a set of principles that guide individuals or societies in determining what is right or wrong, good or bad, and desirable or undesirable. We define the set of Moral Values based on the Moral Foundations Theory Graham et al. ( 2018 ) , which includes Care/Harm, Fairness/Cheating, Loyalty/Betrayal, Authority/Subversion, and Purity/Degradation.

Human Values :
Human values are defined based on the Schwartz Theory of Basic Values Schwartz ( 1992 ) , encompassing Conformity, Tradition, Security, Power, Achievement, Hedonism, Stimulation, Self-Direction, Universalism, and Benevolence. These values represent desirable goals in human life that guide the selection or evaluation of actions and policies.

Building upon the network from the previous stage, we establish connections between users and their associated values in an undirected manner. This connection type offers two key benefits. Firstly, it introduces shortcuts between users who share similar beliefs or mindsets, facilitating the propagation of information across distant nodes. Secondly, it allows the prediction results of user responses to potentially be attributed to the belief nodes (instead of past utterances), thereby enhancing the explainability of the process.