Artículo
Analyzing mass media influence using natural language processing and time series analysis
Fecha de publicación:
07/2020
Editorial:
IOP Publishing
Revista:
Journal of Physics: Complexity
ISSN:
2632-072X
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
A key question of collective social behavior is related to the influence of mass media on public opinion. Different approaches have been developed to address quantitatively this issue, ranging from field experiments to mathematical models. In this work we propose a combination of tools involving natural language processing and time series analysis. We compare selected features of mass media news articles with measurable manifestation of public opinion. We apply our analysis to news articles belonging to the 2016 US presidential campaign. We compare variations in polls (as a proxy of public opinion) with changes in the connotation of the news (sentiment) or in the agenda (topics) of a selected group of media outlets. Our results suggest that the sentiment content by itself is not enough to understand the differences in polls, but the combination of topics coverage and sentiment content provides an useful insight of the context in which public opinion varies. The methodology employed in this work is far general and can be easily extended to other topics of interest.
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Articulos(ICC)
Articulos de INSTITUTO DE INVESTIGACION EN CIENCIAS DE LA COMPUTACION
Articulos de INSTITUTO DE INVESTIGACION EN CIENCIAS DE LA COMPUTACION
Articulos(IFIBA)
Articulos de INST.DE FISICA DE BUENOS AIRES
Articulos de INST.DE FISICA DE BUENOS AIRES
Articulos(IIEP)
Articulos de INST. INTER. DE ECONOMIA POLITICA DE BUENOS AIRES
Articulos de INST. INTER. DE ECONOMIA POLITICA DE BUENOS AIRES
Citación
Albanese, Federico; Pinto, Sebastián; Semeshenko, Viktoriya; Balenzuela, Pablo; Analyzing mass media influence using natural language processing and time series analysis; IOP Publishing; Journal of Physics: Complexity; 1; 2; 7-2020; 1-13
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