Quantitative and Qualitative Methods Lab (QQM Lab)

The Quantitative and Qualitative Methods Lab (QQM Lab) is a laboratory for the analysis of language, discourse and multimodality.

We recognize the importance of gaining a comprehensive understanding of discursive phenomena by comparing the results obtained from applying different analytical methods through a process of triangulation. Mixed methods discourse analysis integrates quantitative and qualitative data, as well as analytical techniques, to provide a more comprehensive understanding of discourse. This combination allows us to explore both the what (for example, which words or phrases are frequently used) and the why or how (for example, why these words are used and how they influence meaning). The application of quantitative and qualitative approaches also provides more robust results when analyzing multimodal texts that combine various semiotic systems, as is the case with many texts disseminated on social and/or digital media.

In the field of quantitative methodologies, we are particularly interested in applications of corpus linguistics (Sketch Engine), semantic tagging (Wmatrix), topic modeling (Iramuteq), data analysis using R, and techniques for studying reading and writing processes, such as eye-tracking and keystroke tracking. With a view to sharing the latest trends in research, each year we offer a series of in-person and online training seminars on various tools for the quantitative analysis of texts and their applications to real-world cases.

Furthermore, we believe it is important to complement quantitative analysis with qualitative methods to study discourse in real-world contexts. To this end, we use platforms such as MaxQda for coding qualitative data, mixed methods analysis, and data visualization. In recent studies, researchers in Public discourse have applied mixed methods to topics as varied as misogyny in politics, the development of legal language,  the representation of current armed conflicts in the press of different countries, the role of emotions in discourse, and the development of academic writing among English and Spanish language learners in schools and universities. 

PhD theses supervised by members of the group have applied corpus linguistics methodologies in combination with pragmatics, metaphor studies and Appraisal theory, and technologies such as eye-tracking and keystroke tracking have been used to beter understand reading and writing processes.