基于决策偏移的舆论演化动力学模型

随着社会计算的飞速发展，网络数据日益向大数据方向演进，网络群体呈现出多样性特征. 针对传统舆论演化动力学模型忽略大规模群体一致性压力和个体决策内驱力的相互作用，以及社会网络节点多、规模大等问题，提出了基于决策偏移概念的舆论演化动力学模型. 模型将内在偏移牵引力、外在群体一致性压力相结合，并引入社会心理学从众效应理论，建立依从、趋同和内化的节点状态及状态转移策略和观点演化策略. 仿真结果表明，模型能够有效模拟观点的收敛和分化，与经典有限信任模型相比，更加符合大型社会网络中群体舆论演进和个体交互的行为特征，揭示了群体层面观点演化的内在规律，为大数据时代分析现实舆论形成的内在机理提供理论模型和参考.

Decision offset based dynamics opinion model

With the rapid development of social computing, the increasing data scale in network is evolving as big data orientation while the community in network is presenting as multiple characteristics. In traditional opinion model, the group uniformity pressure and individual driving force are not considered, thus impact the efficiency of large scale nodes analysis. In this paper, a decision offset based dynamics opinion model (DO2M) is proposed. This model can establish state transfer and three kinds of opinion decision for opinion formation analysis with considering multiple factors which are internal expectation traction、external group uniformity pressure and herding effect. Simulations results show DO2M can simulate unification and polarization of opinion well. Compare to Deffuant model, DO2M is more correspond to the characteristics of opinion formation and individual interaction. Further, DO2M can reveal internal disciplines of opinion and also can be referred to the big data analysis in opinion formation.