The epidemiological outbreak of a novel coronavirus (2019-nCoV or Covid-19) in China, and its rapid spread, gave rise to the first pandemic in the digital age. Derived from this fact that has surprised humanity, many countries started with different strategies in order to stop the infection. In this context, one of the greatest challenges for the scientific community is monitoring (real time) the global population to get immediate feedback of what is happening with the people during this public health contingency. An alternative interesting and affordable for the materialization of the aforementioned is the social media. In a social network, the people can act as sensors that provide information not only of personal data, including health, but also data derived from their behavior. This paper aims to analyze the publications of people in Mexico using a text mining approach. Specifically, Mexico City is presented as a case study to help understand the impact on society of the spread of Covid-19.