The Laboratory for Collective Narratives and Discourse Analysis (LACONDA) aims to support its partners in structuring, exploring, and analyzing the textual data at their disposal, and to provide them with tools for its interpretation. Drawing on methodologies and computational processes developed by researchers in the field of natural language processing, this laboratory works with the Montréal Observatory of Social Issues to better understand the aspirations and challenges of Montréal’s citizens, at the neighbourhood and community levels.
Beyond supporting the analysis of textual data already shared by the partners, LACONDA will be able to collect, process, and analyze new textual datasets on relevant issues. For instance, we will analyze media discourses in Montréal in order to understand the evolution of narratives, values, and “feelings” linked to specific themes in the public sphere using automated information extraction processes and narrative sequences.
Our ability to understand and assess social issues relies on several types of media artifacts, some of which are difficult to analyze objectively. For example, citizens express their views on social media, in open letters, or in public forums; they produce posters, flyers, or slogans. The challenge lies in the sample size, which should be as comprehensive as possible to ensure that it represents the overall discourse.
These ephemeral discursive productions are not readily incorporated into data columns. At best, certain partners will have conducted structured surveys to collect testimonials and opinions that would then be compiled and, in some cases, stored in a spreadsheet. In any case, the analysis of discourses produced by citizens requires considerable resources, the implementation of analytical methodologies, the convening of experts, and major precautions to avoid bias in the interpretation of collected opinions.
LACONDA will establish relationships with other laboratories conducting similar research in various disciplines (including political science, philosophy, and cognitive science), in addition to teaching at the undergraduate and graduate levels and conducting research related to the work being done. It will also strive to plan analytical processes and address requests from partners.
Students will be trained as research assistants in the laboratory for pedagogical purposes. They will perform all tasks related to the extraction and gathering of textual data (web scraping), its pre-processing (cleaning and structuring), and its analysis. They will also produce graphics to help people understand their findings.