Department of Management, Nanjing University of Posts and Telecommunications, Nanjing, China.
Jiangsu University Philosophy and Social Science Key Research Base-Information Industry Integration Innovation and Emergency Management Research Center, Nanjing, China.
Big Data. 2024 Apr;12(2):100-109. doi: 10.1089/big.2022.0271. Epub 2023 May 29.
Public persons are nodes with high attention to public events, and their opinions can directly affect the development on events. However, because of rationality, the followers' acceptance to the public persons' opinions will depend on the information trait on public persons' opinions and own comprehension. To study how different opinions of the public persons guide different followers, we build an opinion dynamics model, which would provide a theoretical method for public opinion management. Based on the classical bounded confidence model, we extract the information quality variables and individual trust threshold and introduce them to construct our two-stage opinion evolution model. And then in the simulation experiments, we analyze the different effects of opinion information quality, opinion release time, and frequency on public opinion by adjusting the different parameters. Finally, we added a case to compare real data, the data from classical model simulation and the data from improved model simulation to verify the effectiveness on our model. The research found that the more sufficient the argument and the more moderate the attitude, the more likely to guide the public opinion. If public person holds different opinions and different information quality, he should choose different time to present his opinion to achieve ideal guide effect. When public person holds neutral opinion and the information quality is relatively general, he/she can intervene in public opinion as soon as possible to control final public opinion; when public person holds extreme opinion and the information quality is relatively high, he/she can choose to express opinion after a certain period on public opinion evolution, which is conducive to improve the guidance effect on public opinion. The frequency of releasing opinions of public person consistently has a positive impact on the final public opinion.
公众人物是对公共事件关注度较高的节点，他们的意见可以直接影响事件的发展。然而，由于理性的存在，追随者对公众人物意见的接受程度将取决于公众人物意见的信息特征和自身的理解。为了研究公众人物的不同意见如何引导不同的追随者，我们构建了一个意见动态模型，为公众舆论管理提供了一种理论方法。基于经典的有界置信模型，我们提取了信息质量变量和个体信任阈值，并引入它们来构建我们的两阶段意见演化模型。然后，在模拟实验中，我们通过调整不同的参数，分析了意见信息质量、意见发布时间和频率对公众意见的不同影响。最后，我们添加了一个案例来比较真实数据、经典模型模拟数据和改进模型模拟数据，以验证我们模型的有效性。研究发现，论点越充分，态度越温和，越有可能引导公众舆论。如果公众人物持有不同的意见和不同的信息质量，他应该选择不同的时间来表达自己的意见，以达到理想的引导效果。当公众人物持有中立意见且信息质量相对一般时，他可以尽快干预公众舆论，以控制最终的公众舆论；当公众人物持有极端意见且信息质量较高时，他可以选择在公众舆论演变一段时间后表达意见，这有利于提高对公众舆论的引导效果。公众人物发表意见的频率对最终公众舆论始终有积极的影响。
