The objective of this end of degree project has been to develop a system that enables it to obtain commit comments from GitHub in order to be analyzed as sentiment. First of all the procedure needs to gather a large number of commit comments to be able to draw some accurate conclusions. To pursue this task, we have used multiple tools, each of them has been described in this study. They are GHTorrent (through its website or mongoDB) and another one developed by myself through Python and with requests to the API GitHub. Once the data has been obtained, it has been analyzed through Senpy. Later the result including its corresponding data has been stored using Elasticsearch. This data is formed by the repository name in which the commit comment has been made, the time they had been issued... After the data has been stored in Elasticsearch, it is finally possible to visualize the results by creating a dashboard by using Sefarad and Web Components, which offers a good interface for the user. Once all the elements can be visualized in the dashboard, these findings allow the user to draw his own conclusions about sentiments and programming languages as well as other features.