ECUE Bibliometrics

Code de l'ECUE : IMEX110

Ce cours appartient à UE Bibliometrics (3 ECTS) qui contient 1 ECUE

Structure

EUR ELMI

Domaine disciplinaire

Sciences économiques

Lieu d'enseignement

Campus Saint Jean d'Angély

Niveau du cours

Master 1 , Master 2

Semestre

Semestre pair

Langue

Anglais

PRESENTATION

Social network analysis is used for various purposes, from marketing and international economics to recommendation algorithms. The main objective of this course is to teach students how to use social network analysis and give them the tools to apply it to a subject that interests them.

For this course, we will focus on one particular application of social network analysis: knowledge production. This type of analysis is used in economics of science, economics of innovation, and all epistemology-related fields. In addition to basic network analysis and indicators, the student will be introduced to many subjects such as data collection, cluster detection algorithms, spatialization algorithms, and data visualization.

While, at its core, the course will give students the necessary technical skills to apply social network analysis to any topic, we will provide an overview of how such tools are used to study knowledge production in the contemporary scientific literature in scientometrics and epistemology.

Responsable(s) du cours

Alexandre Truc

Présentiel

20h de cours magistral

PREREQUIS

Avant le début du cours, je dois ...

For this course, one computer per student is required. Students should install R and R Studio before starting the course. To do so, follow these steps:
[1] Install R using the following links: Windows: https://cran.r-project.org/bin/windows/base/ Mac: https://cran.r-project.org/bin/macosx/
[2] Install R studio: Follow the link and choose your OS (Mac or Windows) at the bottom: https://posit.co/download/rstudio-desktop/

OBJECTIFS

A la fin de ce cours, je devrais être capable de...

The main objective of this course is to teach students how to use social network analysis and give them the tools to apply it to a subject that interests them.

CONTENU

Session 1: introduction to network analysis and R

After a brief introduction to network analysis, with an emphasis on scientometrics, the student will be introduced to R, an open-source software program.
Session 2 and 3: basic R, data collection and preparation

Using an open source database, students will be introduced to data collection, cleaning, and structuration. This will ensure that students are autonomous in the pursuit of their own quantitative studies as everything will be accessible to them after the course.
Session 4: descriptive statistics and basic scientometrics indicators

Basic R on how to conduct a quantitative analysis of published documents.
Session 5 and 6: introduction to tidygraph and graph construction

Using tidygraph R package, students will learn how to construct and manipulate graph objects in R. The goal is to easily and rapidly produce visualizations of graphs to introduce social network analysis concepts in an intuitive manner.
Session 7 and 8: graph analysis

Using the graph objects constructed in previous sessions, the student will learn how to conduct quantitative analysis. Most notably, they will learn about cluster detection algorithms to go beyond the intuitive visual analysis of graphs.
Session 9: plotting and data visualization

Introduction on to how to present quantitative results in a compelling manner

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Important

Ce syllabus n’a aucune valeur contractuelle. Son contenu est susceptible d’évoluer en cours d’année : soyez attentifs aux dernières modifications.