In recent years, in all fields of knowledge, a data-driven approach has spread according to the new scenario defined by the Big Data era. The so-called data deluge has started a season where an impressive amount of data constitutes a valuable research material for scholars. In this new context, the data-driven approach enables academics and scientists to examine and organize data with the goal of increasing knowledge in many research areas. The deluge of data today allows us to plan new analyses on a variety of unstructured data that are produced in major part by web navigation. Recent estimates maintain that 80% of all data is textual data. Furthermore, information that comes from social networks and social media, like Facebook, Twitter, and Instagram, produces unstructured data in real time.Unstructured data is not organized according to a predefined scheme, and information resulting from these sets of data is typically text-heavy. Anyway, it may contain data such as dates, numbers, and facts as well. This results in irregularities and ambiguities that make it difficult to understand their meaning using traditional programmes as compared to data stored in structured databases. This flow of data has allowed the development of new methods and models, i.e. sentiment analysis to measure the mood of individuals and capture gender differences in language. Sentiment analysis, which is also called opinion mining, has been one of the most active research areas in natural language processing since early 2000 (Liu, 2015), and the constant refinement of analytical tools is offering a richer array of opportunities to analyse these data for many different purposes.These broad assets of data are nowadays available and largely accessible. They represent both a strategic opportunity and a powerful challenge for researchers enabling them to find out new paths for social life exploration, and, more specifically, for the comprehension of the complex relationships intersecting some key concepts in gender, feminist and women/ men sexual identity studies.Data is mainly textual and produced by fertile human communication and exchange activities that take place on an increasing number of social platforms with a powerful viral potential. Human relationships are shaped at different levels of abstraction, fluctuating in the virtual space of the web-net. In these virtual spaces people are actively engaged, performing their agency, and managing their voice contributing to the 'reproduction of or the resistance to gender arrangements' in a community (Holmes & Meyerhoff, 1999:180). For this reason, it is worth studying how the concept of gender is built in the social practice of everyday life through multiple interactions, on the one sideand how it intersects other concepts and dimensions of the same research field, on the other. The Community of Practice approach, proposed by Holmes and Meyerhoff (1999), is actually compatible with the social-constructionist theory.This new kind of data has also changed qualitative research in gender studies...