An opinion dynamics model for unrelated discrete opinions

Unrelated discrete opinions can be generally found in social media-based data about a certain topic, which cannot be well measured and analyzed using existing opinion dynamics models. To fill this gap, this study proposes a new discrete opinion dynamics model based on the sentiment–opinion transformation mechanism. In the model, a matrix formulating the transformation relationship between sentiments and opinions is considered. In addition, the model is initialized based on an initial-sentiment matrix of the information instead of a certain mathematical distribution. Subsequently, we design the simulation experiments using different values of parameters and different network topologies to study four effects on sentiment and opinion dynamics, namely, the effects of the threshold, the effects of the initial-sentiment matrix, the effects of the sentiment–opinion matrix, and the effects of the second piece of information. The results highlight the importance of transformation relation between sentiment and opinion.