This study aims to analyze the level of anger developed by drivers in Mexico City and also understand the behavior that those drivers use to express that anger, using four different survey methods. The first focuses on personal information, the second Driving Anger Expression Inventory (DAX), the third refers to a shorten version of Driving Anger Scale (DAS) and the fourth being the Dula Dangerous Driving Index (DDDI). These have previously been applied and validated in several different countries. The questionnaires were filled out online by 626 drivers. Using the data collected through the online platform, it was possible to identify the kind of reactions volunteers displayed while driving. Also, it was possible to identify that people in Mexico City developed anger depending on their driving area. Our analyses shows that in the Adaptive/Constructive Expression subscale, males and females show a significant difference in their mean score, with women express their anger in a more constructive way than males.

The most unexpected and toughest phenomenon that has occurred in recent times is the global COVID-19 pandemic. One of the first measures to prevent the spread of the disease was to close educational institutions. The students were forced to start a learning process through social networks and web platforms. In some countries, a return to face-to-face classes was established. However, weeks later, some of them had to return to virtual activities due to an upswing in the COVID-19 cases. In Mexico, classes have been held virtually, with face-to-face activities only re-established in two of the 32 states. In our state, Yucatan, scholarly activities are still virtual. In this work, the dispersion of COVID-19 at different academic establishments in Yucatan was simulated. Networks of Friendship, noncordial treatment, family ties and study groups were considered. Based on these networks, we evaluated the possibility of returning to school without inducing a rebound in the COVID-19 cases in the state. Agent-based simulations were used, with each student as an agent. Interaction rules were established based on international research regarding good practices in times of COVID-19. We used seven networks from different academic institutions, ranging from primary through college level. As a result, possible contagion curves were obtained for different scenarios, which leads to a discussion about the measures that would be relevant once a return to face-to-face classes is overseen. Simulations show that isolating students and reducing the number of students in the same classroom are good strategies and substantially reduce the possible contagiousness.

We use complex network theory to study the differences between the friendship concepts in elementary school and university students. Four friendship networks were identified from surveys. Three of these networks are from elementary schools; two are located in the rural area of Yucatán and the other is in the urban area of Mérida, Yucatán. We analyzed the structure and the communities of these friendship networks and found significant differences among those at the elementary schools compared with those at the university. In elementary schools, the students make friends mainly in the same classroom, but there are also links among different classrooms because of the presence of siblings and relatives in the schools. These kinds of links (sibling-friend or relative-friend) are called, in this work, “mixed links”. The classification of the communities is based on their similarity with the classroom composition. If the community is composed principally of students in different classrooms, the community is classified as heterogeneous. These kinds of communities appear in the elementary school friendship networks mainly because of the presence of relatives and siblings. Once the links between siblings and relatives are removed, the communities resembled the classroom composition. On the other hand, the university students are more selective in choosing friends and therefore, even when they have friends in the same classroom, those communities are quite different to the classroom composition. Also, in the university network, we found heterogeneous communities even when the presence of sibling and relatives is negligible. These differences made up a topological structure quite different at different academic levels. We also found differences in the network characteristics. Once these differences are understood, the topological structure of the friendship network and the communities shaped in an elementary school could be predicted if we know the total number of students and the ties between siblings and relatives. However, at the university, we cannot do the same. This discovery implies that friendship is a dynamic concept that produces several changes in the friendship network structure and the way that people make groups of friends; it provides the opportunity to give analytic support to observational studies. Communities were also studied by gender and we found that when the links among relatives and siblings were removed, the number of communities formed by one gender alone increased. At the university, many communities formed by students of the same gender were also found.