的计算：网络中的存水点不是孤立的，为了对其相互影响建模，可以先将存水点

Calculation: The water storage points in the network are not isolated. In order to model their mutual influence, the water storage points can be divided into several categories. Through interaction, the classification of the water storage points will change. In order to introduce differences in people, it can be assumed that the water storage points have different thresholds. Only when the impact is strong enough can they be affected by nearby water storage points. In order to introduce the diversity of thoughts to be spread, the preference of water storage points can be divided into spatial (the closer you are, the better) and hedonic (the more the better), combined with different network structures, you can target the network The propagation of water is modeled in different ways. <br>2. People do not interact with each other only once. Markov chains reflect the impact of different interactions on individuals, while random walk and path dependence can be seen as the two extremes of the mode produced by continuous interaction between people . The result of interaction may be cooperation or mutual entrapment. Among them, it is necessary to introduce game theory, introduce cost signal in economics, and introduce group selection and fame to explain why cooperation is possible. <br>3. For example, the Markov chain can analyze the relationship between before and after speech, and the information dissemination model can predict the result of voting

Calculation of: the water storage points in the network are not isolated. In order to model their interaction, the water storage points can be divided into several categories. Through interaction, the classification of water storage points will change. In order to introduce people's differences, It can be assumed that water storage points have different thresholds, and only when the impact is strong enough will it be affected by nearby water storage points. In order to introduce the diversity of ideas to be spread, the preference of water storage points can be divided into spatial (the closer to yourself, the better) and hedonic (the more the better), combined with different network structures, we can model the propagation of water on the network in different ways.<br>2. People do not interact only once. Markov chain reflects the impact of different interactions on individuals, while random walk and path dependence can be regarded as the two extremes of the model generated by people's continuous interaction. The result of interaction may be cooperation or mutual entrapment, which requires the introduction of game theory, the introduction of cost signal in economics, and the introduction of group selection and reputation to explain why cooperation is possible.<br>3. For example, Markov chain can analyze the relationship between before and after speeches, and the model of information dissemination can predict the voting results

Calculation: Water storage points in the network are not isolated. In order to model their interaction, water storage points can be divided into several categories. Through interaction, the classification of water storage points will change. In order to introduce different people, it can be assumed that water storage points have different threshold, and only when the influence is strong enough will it be affected by nearby water storage points. In order to introduce the diversity of ideas to be spread, the preference of water storage points can be divided into spatial (the closer to yourself, the better) and hedonic (the more, the better). Combined with different network structures, we can model the water spread on the network in different ways. 2. People don't interact only once, Markov chain reflects the influence of different interactions on individuals, while random walk and path dependence can be regarded as the two extremes of the pattern generated by the continuous interaction between people. The result of interaction may be cooperation or mutual harm, which requires the introduction of game theory, signaling model in economics, group choice and fame to explain why cooperation is possible. 3. For example, Markov chain can analyze the relationship between speeches before and after, and the model of information dissemination can predict the voting result.