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Assessing the spread of Keynesian ideas in the economic policy debate: a Text Mining approach on Twitter

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Assessing the spread of Keynesian ideas in the economic policy debate: a Text Mining approach on Twitter

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dc.contributor.author Perfetto, Chiara es_ES
dc.contributor.author Rancan, Antonella es_ES
dc.contributor.author Resce, Giuliano es_ES
dc.date.accessioned 2024-01-11T10:40:38Z
dc.date.available 2024-01-11T10:40:38Z
dc.date.issued 2023-09-22
dc.identifier.isbn 9788413960869
dc.identifier.uri http://hdl.handle.net/10251/201778
dc.description.abstract [EN] This paper proposes a methodology for examining the presence of Keynesian ideas in the economic debate. To this aim we use Twitter as a source of data to monitor the debate in real time. We quantify the presence of Keynesian and anti-Keynesian thought in tweets about the economy and we qualify the emotional tone of these tweets. Our preliminary results show that the 20 per-cent of total English tweets about #economy contain words related to Keynes while about 8 per- cent contain words referring to anti-Keynesian policies. The monthly analysis of the tweets shows a certain heterogeneity. The distribution of Keynes-related tweets is much more uneven than the distribution of anti-keynesian tweets. Our evidence suggests that the methodology we applied to understand how much of the Keynesian thought is still around in the economic debate can be promising. The next step will be to focus on georeferenced tweets to detect heterogenity across countries and to understand how country-level trends reflect the economy cycle. This study still has some limitations that will be faced in future research such as the classification of topics and the focus on English texts for the moment. es_ES
dc.format.extent 9 es_ES
dc.language Inglés es_ES
dc.publisher Editorial Universitat Politècnica de València es_ES
dc.relation.ispartof 5th International Conference on Advanced Research Methods and Analytics (CARMA 2023)
dc.rights Reconocimiento - No comercial - Compartir igual (by-nc-sa) es_ES
dc.subject Text Mining es_ES
dc.subject Twitter es_ES
dc.subject Keynesian thought es_ES
dc.title Assessing the spread of Keynesian ideas in the economic policy debate: a Text Mining approach on Twitter es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.4995/CARMA2023.2023.16432
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Perfetto, C.; Rancan, A.; Resce, G. (2023). Assessing the spread of Keynesian ideas in the economic policy debate: a Text Mining approach on Twitter. Editorial Universitat Politècnica de València. 129-137. https://doi.org/10.4995/CARMA2023.2023.16432 es_ES
dc.description.accrualMethod OCS es_ES
dc.relation.conferencename CARMA 2023 - 5th International Conference on Advanced Research Methods and Analytics es_ES
dc.relation.conferencedate Junio 28-30, 2023 es_ES
dc.relation.conferenceplace Sevilla, España es_ES
dc.relation.publisherversion http://ocs.editorial.upv.es/index.php/CARMA/CARMA2023/paper/view/16432 es_ES
dc.description.upvformatpinicio 129 es_ES
dc.description.upvformatpfin 137 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela OCS\16432 es_ES


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