The course describes different typical situations justifying recourse to computer analysis and presents the main steps of such analyses (analysis of needs, choice of software or of procedures answering to the identified needs, application of the elaborated analysis procedure). Special attention will be paid to the practical application of this software through exercises on concrete cases : screening and formatting texts, finding and extracting information, statistical word processing, etc.
The contribution of this Teaching Unit to the development and
command of the skills and learning outcomes of the programme(s) can be
accessed at the end of this sheet, in the section entitled
“Programmes/courses offering this Teaching Unit”.
At the end of this learning unit, the student is able to :
Specialists in social sciences are often faced with situations where they must work with large amounts of textual data (literary, historical, or political texts; linguistic research data, etc.). Computer tools offer undeniable advantages for the analysis, organization, sorting or formatting of this information. One should thus be able to master these tools and select an appropriate approach method. The aim of this course is to provide students with the key to choosing and using methods of analysis adapted to different contexts of textual data processing.
More specifically, the course aims to allow students to :
1) select, use, and possibly adapt or conceptualise specialised computer tools in the field of textual data processing;
2) perceive and criticise the particularities and limits of specialised software;
3) become acquainted with the intellectual procedure implied by recourse to data processing in the social sciences.
Classes are divided between lectures presenting the tools and methods, and tutorials aiming to allow students to experiment with methods and software.
Title of the programme
Master  in Linguistics
Master  in French and Romance Languages and Literatures : French as a Foreign Language
Master  in Anthropology
Master  in Information and Communication Science and Technology
Master  in Ancient and Modern Languages and Literatures
Master  in data Science: Statistic