Forecasting consumer confidence through semantic network analysis of online news-Reference-Cited by-同舟云学术

Forecasting consumer confidence through semantic network analysis of online news

Published:2023-07-21 Issue:1 Volume:13 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Fronzetti Colladon Andrea^ORCID,Grippa Francesca,Guardabascio Barbara,Costante Gabriele,Ravazzolo Francesco

Abstract

AbstractThis research studies the impact of online news on social and economic consumer perceptions through semantic network analysis. Using over 1.8 million online articles on Italian media covering four years, we calculate the semantic importance of specific economic-related keywords to see if words appearing in the articles could anticipate consumers’ judgments about the economic situation and the Consumer Confidence Index. We use an innovative approach to analyze big textual data, combining methods and tools of text mining and social network analysis. Results show a strong predictive power for the judgments about the current households and national situation. Our indicator offers a complementary approach to estimating consumer confidence, lessening the limitations of traditional survey-based methods.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

https://www.nature.com/articles/s41598-023-38400-6.pdf

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