Forecasting consumer confidence through semantic network analysis of online news

This 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 appea...

Descripción completa

Detalles Bibliográficos
Autores principales: Fronzetti Colladon, Andrea, Grippa, Francesca, Guardabascio, Barbara, Costante, Gabriele, Ravazzolo, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362014/
https://www.ncbi.nlm.nih.gov/pubmed/37479764
http://dx.doi.org/10.1038/s41598-023-38400-6
_version_ 1785076327991214080
author Fronzetti Colladon, Andrea
Grippa, Francesca
Guardabascio, Barbara
Costante, Gabriele
Ravazzolo, Francesco
author_facet Fronzetti Colladon, Andrea
Grippa, Francesca
Guardabascio, Barbara
Costante, Gabriele
Ravazzolo, Francesco
author_sort Fronzetti Colladon, Andrea
collection PubMed
description This 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.
format Online
Article
Text
id pubmed-10362014
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-103620142023-07-23 Forecasting consumer confidence through semantic network analysis of online news Fronzetti Colladon, Andrea Grippa, Francesca Guardabascio, Barbara Costante, Gabriele Ravazzolo, Francesco Sci Rep Article This 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. Nature Publishing Group UK 2023-07-21 /pmc/articles/PMC10362014/ /pubmed/37479764 http://dx.doi.org/10.1038/s41598-023-38400-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Fronzetti Colladon, Andrea
Grippa, Francesca
Guardabascio, Barbara
Costante, Gabriele
Ravazzolo, Francesco
Forecasting consumer confidence through semantic network analysis of online news
title Forecasting consumer confidence through semantic network analysis of online news
title_full Forecasting consumer confidence through semantic network analysis of online news
title_fullStr Forecasting consumer confidence through semantic network analysis of online news
title_full_unstemmed Forecasting consumer confidence through semantic network analysis of online news
title_short Forecasting consumer confidence through semantic network analysis of online news
title_sort forecasting consumer confidence through semantic network analysis of online news
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362014/
https://www.ncbi.nlm.nih.gov/pubmed/37479764
http://dx.doi.org/10.1038/s41598-023-38400-6
work_keys_str_mv AT fronzetticolladonandrea forecastingconsumerconfidencethroughsemanticnetworkanalysisofonlinenews
AT grippafrancesca forecastingconsumerconfidencethroughsemanticnetworkanalysisofonlinenews
AT guardabasciobarbara forecastingconsumerconfidencethroughsemanticnetworkanalysisofonlinenews
AT costantegabriele forecastingconsumerconfidencethroughsemanticnetworkanalysisofonlinenews
AT ravazzolofrancesco forecastingconsumerconfidencethroughsemanticnetworkanalysisofonlinenews

Ejemplares similares