Description: Linguistic anonymization is the process of modifying textual data in such a way that characteristics that could identify specific individuals are removed or altered. This process involves transforming names, places, and other identifying elements in the text using techniques such as substitution, generalization, or perturbation. The main objective of linguistic anonymization is to protect individuals’ privacy while allowing data analysis. This approach is particularly relevant in the context of growing concerns about data privacy in the digital age, where personal information can be easily collected and analyzed. Linguistic anonymization applies not only to raw data but also to texts generated in various contexts, including research, surveys, and market studies, where identifying participants could compromise their privacy. By implementing this technique, the aim is to balance the utility of data for research and analysis with the need to protect the identity of the individuals involved. In summary, linguistic anonymization is a crucial tool in data management that enables the responsible and ethical use of textual information without sacrificing individuals’ privacy.
