Netnography involves observing the interactions and relationships that compete in the digital environment in order to understand how society acts, one of the ways to make these observations is to analyze the data that people publish on social networks. This work developed a web crawler for the FragUrb and Dataluta projects in such a way that the tool created was also able to bring together the areas of human sciences and exact sciences, where such an achievement was only feasible from the partnership between the Interdisciplinary Laboratory in Technologies, Education and Computing (LITEC) from the Federal University
of Pará (UFPA) with the Universidade Estadual Paulista (UNESP), focusing on the Twitter social network to collect data from posts made from a search term and store them in a database of NoSQL data, making its visualization available from a web platform. The resources used for the development of the work were the python 3.9 programming language and its libraries and for the database we used MongoDB. The methodological approach consisted, initially, in a broad research of works directed to broaden the understanding of the state of the art and the state of practice aimed at the elaboration of a twitter crawler,
deepening the research on the Application Programming Interface (API) twitter and issues related to the use of more appropriate tools for Social Network Analysis; from this knowledge construction it was possible to develop the tool's script and integrate it to a web platform. The crawler was successful in obtaining data for the two fronts of the project, tests were implemented in order to use the search data to carry out a data analysis to obtain insights into the behavior of people who publish on this network, it was possible to map the post and find the most influential users according to the chosen term, as was the case with the search for the term #foraBolsonaro where it was possible to obtain 3815 Tweets and 7363
Retweets. The developed tool was of great value to the researchers focused on the Netnography of the FragUrb and Dataluta projects, because by automating the capture of a large amount of data, it makes available the visualization of these samples for application in their geographic analyses, which are fundamental for the understanding of the relationships of individuals, events and roles with which communities influence the digital world.
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