Training workshop by Francisco Villarroel Ordenes

LOURIM Louvain-La-Neuve, Mons

May 09, 2022

May 10, 2022

9.30 am - 5 pm


Ateliers FUCaM - Salle 11

Training workshop: “Text mining methods for business and management research”


Learning objectives:

This high-density workshop is focused on text mining methods, processes, and tools for business and management research. It is designed to prepare researchers for the conceptual and empirical challenges
involved in the use of big (unstructured) data, from text-data gathering, measurement, and modelling. It is practical
in nature, giving participants a state-of-the-art overview of the text mining approaches and methods, while
providing many opportunities for methodological practice. The workshop is also aimed at teaching and practicing
advanced research skills (e.g., generating interesting testable hypotheses, manuscript positioning). While the
workshop is geared towards marketing, it can also be applied to other business and management fields.



This interactive workshop is built on prior reading of recent text mining guides, empirical applications of
text mining, and hands-on work. The workshop includes three main parts: 1) Introduction to Text Mining
Methods (2 hours), 2) Dictionary Methods (5 hours) and 3) Machine Learning (5 hours). Each unit includes
theoretical lectures on natural language processing, empirical applications, and hands-on work using public datasets
available from social media platforms (Twitter) and review sites (e.g., YELP).


Target audience:

The workshop is aimed at PhD students and research staff with a background in management,
business, and/or marketing. Basic knowledge of statistics and machine learning is recommended. The number of
participants will be limited to create a stimulating environment.



The KNIME Analytics Platform will be used as the main analytics software, together with integrations
of R and/or Python. Participants will need to install all required software and extension before attending. The use of a laptop with at least 16GB RAM is highly recommended.



The workshop is worth 2 ECTS


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