Online opinion dynamics model considering derivative topics based on complex network
研究原始话题与衍生话题在双层复杂网络中的交互如何影响在线舆论演化，通过仿真实验发现话题关联度和相对影响力是关键因素，对舆论治理有参考价值。
Purpose In social networks, derivative topics derived from original topics are becoming increasingly general, and the interaction between derivative topics and original topics makes public opinions increasingly complex and unstable. This paper aims to study the evolution of online opinions under the interaction between original and derivative topics. Design/methodology/approach This paper establishes an online opinion dynamics model based on a two-layer complex network, consisting of original and derivative topic layers. In the two-layer network, the interaction threshold between netizens and the external environment is set dynamically. Secondly, by setting herd mentality, response subject, and media parameters, the internal psychological factors and external environmental factors are involved in the model. Finally, simulation experiments are conducted using actual online social network data to examine the effects of topic adherence, relative clout of topics, and external environmental information on the opinions related to the original and derivative topics. Findings Topic relationships are crucial in the interaction between original and derivative topics. Derivative topics that are highly related to the original topic will have a greater impact on each other’s dissemination. Those with high relative clout can influence the original topic more rapidly. Therefore, when encountering derivative topics that are highly related to the original topic or have high relative clout, relevant departments should give greater and more timely attention. In addition, due to topic relationships, governing a single topic always leads to an increase in negative opinions on another topic, which may turn low-clout topics into high-clout ones. Thus, the response subject can actively explore the commonalities between derivative and original topics and intervene in common issues to enhance effectiveness. Research limitations/implications First, our model did not consider forgetting mechanisms and node decay effects which may affect the long-term dissemination of information and the intensity of interaction between nodes. Second, we treat the response subject’s credibility and information quality as fixed parameters. Third, we employ a rough estimation method to assess topic adherence. Practical implications Due to topic relationships, the governance of a single topic always leads to an increase in negative opinions on another topic, which may turn low-clout topics into high-clout topics. Thus, the response subject can actively explore the commonalities between the derivative and original topics and intervene in common issues to be more effective. Originality/value This paper explores the interaction scenario between the original and derivative topics, providing valuable insights for more complex public opinion governance issues.