Keywords
Machine learning, Text analysis, Open-ended survey responses
Document Type
Article
Abstract
The rapid digital transformation of society in recent years has resulted in the creation of vast databases available online, particularly benefiting businesses. The main challenge now is to effectively access and utilize this data to make informed business decisions. Artificial intelligence techniques, such as natural language processing and machine learning, have proven highly effective across various domains and present valuable opportunities for developing automated models to extract insights and uncover new information. This paper demonstrates the effectiveness of machine learning techniques in the field of social and economic sciences, focusing specifically on the task of classifying open-ended survey questions. We introduce a machine learning-based solution for verbatim classification, comparing a traditional and deep learning techniques. We use data from a survey conducted during the first lockdown in France to understand elderly adults' perceptions of the Coronavirus crisis.
Recommended Citation
Wannous, Ouban
(2026)
"Machine Learning Based Approaches to Survey Elderly Adults About the Perception of the Coronavirus Crisis,"
Al-Farahidi Expert Systems Journal: Vol. 2:
Iss.
1, Article 3.
DOI: https://doi.org/10.65645/3105-9104.1022
DOI
10.65645/3105-9104.1022