Krawczyk Malgorzata J, Kułakowski Krzysztof
Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Mickiewicza 30, PL-30059 Kraków, Poland.
Entropy (Basel). 2021 Oct 28;23(11):1418. doi: 10.3390/e23111418.
The concept of Heider balance, usually applied to interpersonal relations, is generalized here to opinions gathered in surveys. At first, we compare four algorithms, which drive a matrix dataset to a balanced state. The criterion is that the final state obtained with an algorithm should be as close as possible to the initial state. The result is that deterministic differential equations work better than their Monte Carlo counterparts. Next, we apply the winning algorithms to the matrix of correlations between opinions gathered in American states between 1974 and 1998. The results are interpreted in terms of the classic comfort hypothesis (E. Babbie, 2007).
通常应用于人际关系的海德平衡概念，在此被推广到调查中收集的意见。首先，我们比较了四种算法，这些算法将矩阵数据集驱动到平衡状态。标准是使用一种算法获得的最终状态应尽可能接近初始状态。结果是确定性微分方程比其蒙特卡洛对应方法效果更好。接下来，我们将获胜算法应用于1974年至1998年美国各州收集的意见之间的相关矩阵。结果根据经典的舒适假设（E. 巴比，2007年）进行解释。
