Critical Text Analytics as an Integrative Approach

Session Goals

To define the theoretical foundations of critical text analytics
To appraise the process of crafting computational storylines in critical text analytics research projects
To apply knowledge of critical text analytics in sketching a brief research project

Critical text analytics refers to a discursive approach that employs computational methods to examine collective meaning-making. More than a novel methodology, critical text analytics assumes a collective ontology and a naturalistic epistemology, with distinct potentials for knowledge production in and of the Global South.
Computational storylines are summative statements which capture discursive processes in a significant corpus of text, derived through a mix of quantitative (computational) and qualitative (interpretative) methods. They embody key propositions of a critical text analytics framework by articulating shared meaning-making across collectives while engaging extant complexity within their constituent social constructions.
Case studies of critical text analytics projects highlight the integrated role of lexical, semantic, and discursive analyses to holistically examine collective meaning-making. Distinct applications of critical text analytics principles across varied research questions, methods, and empirical domains emphasize a deeper shared concern for understanding relationships between language and wider social conditions.

(~3 sentences) Select a data corpus of texts that you will analyze, ideally one linked to an ongoing project you are a part of. Describe its basic features, such as how many utterances it contains, who its interlocutors are, and how the data was collected.
(~3 sentences) Articulate a research question you will ask about this dataset and answer through a critical text analytics approach. Explain how this research question is grounded in the underlying principles of a critical text analytics approach.

Montiel, C. J., & Uyheng, J. (2021). Foundations for a decolonial big data psychology. Journal of Social Issues. Advance online publication. https://doi.org/10.1111/josi.12439

Montiel, C. J., Uyheng, J., & Dela Paz, E. (2021). The language of pandemic leaderships: Mapping political rhetoric during the Covid-19 outbreak. Political Psychology, 42(5), 747-766. https://doi.org/10.1002/ejsp.2716

Uyheng, J., & Montiel, C. J. (2021). Populist polarization in postcolonial Philippines: Sociolinguistic rifts in online drug war discourse. European Journal of Social Psychology, 51(1), 84-99. https://doi.org/10.1002/ejsp.2716