In this paper, the authors base on comprehensive approach matching quantitative and qualitative study of political discourse in the field of migration. They report an experiment that they conducted, in which a model for the monitoring of the impact of immigration on the Italian political discourse was developed and tested. The model comprises of a program that performs semantic analysis on a collection of retrieved political speeches related to the phenomenon of immigration, given by two key decision-makers for the immigration policies of Italian public administrations: M. Salvini, the current Minister of Internal Affairs in 2018–2019, and S. Martello, the mayor of the island of Lampedusa. The technique used, the so-called bag-of-words, falls under the established techniques in the sector of natural language processing for the automatic extraction of features from texts. The results obtained by the model were then compared with those accessible through surveys and statistics published by other research on the same phenomenon. Our results are consistent with the findings that derive from the application of other methodologies to the study of immigration. The authors thus believe it might be possible to develop in the future a larger model that allows the monitoring of variations in the attitude towards immigration as a function of the variation in the content of political speeches, and in the results of surveys conducted on the sentiment of the general population on the subject. In its current status, the model allows a data-driven identification of the most prominent factors that influence the minds of political decision-makers with regards to the phenomenon of immigration. In particular, it is determined in the paper whether such factors are primarily socio-cultural or socio-economic factors. © 2020, Russian Academy of Sciences. All rights reserved.