Using Social Network Analysis methodology, specifically the Network of Similarity and Response Time Testing as a survey method, we measured and examined, based on conviction strength, the relationships between beliefs in various conspiracy theories. We employ Social Network Analysis (SNA) to uncover conspiracy thinking patterns. SNA facilitates the disclosure of interdependencies among variables and intricate direct and indirect relationships. The network of conspiracy convictions is mapped and scrutinized to discern the clustering of variables, which is achieved using greedy-modularity algorithms. Structural properties, such as nodal and subgroup density, are subsequently calculated to assess the quality of the clusters. A qualitative evaluation explores the semantic meanings underlying the observed patterns. Our analysis revealed strong correlations between the items, indicating that individuals who believe in one conspiracy theory are highly likely to believe in others. Furthermore, Response Time Testing allowed for measuring the level of people's conviction in these beliefs. We discuss the implications of these findings, suggesting that conspiracy theories may serve as a means for individuals to confirm their positions and feelings in society. This insight calls for a reassessment of strategies to address the spread and impact of conspiracy theories, focusing on understanding the psychological and social factors driving belief in multiple conspiracies and the strength of these convictions.

An experimental real-time hybrid method, which implements the wind response control of a building structure with only a two-way TLMD, is proposed and verified through a shaking table test. The building structure is divided into the upper experimental TLMD and the lower numerical structural part. The shaking table vibrates the TLMD with the response calculated from the numerical substructure，which is subjected to the excitations of the measured interface control force at its top story and an wind-load input at its base. The results show that the conventional method can be replaced by the proposed methodology with a simple installation and accuracy for evaluating the control performance of a TLMD