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Netw. Anal. Min."],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>The omnipresence of the digital ecosystem makes it increasingly important in our societies, which implies that the analysis and study of the digital battlefield in political elections is also becoming more necessary to protect our democracies. Previous literature showed the existence of information operations around the world, designed to manipulate the political perception of citizens, and therefore, the electoral results. This paper examines the Twitter conversation around #14F 2021 Catalonia regional elections, which had special significance due to the pandemic situation and the highly polarized scenario around Catalonia and Spain, using tools and techniques from Big Data Analytics and Artificial Intelligence. The results obtained show that the conversation existed inside robust echo chambers within each political party community, which became even more powerful if parties are unified into political affinity blocks. Also, focusing on the analysis related to the social bot presence, a significant quantity of results showed a higher presence of social bots in VOX party community compared to the rest of communities. This study corroborates other existing studies regarding the Catalan and Spanish scenario on the presence of echo chambers and on the existence of social bots with their tendency to basically amplify content; it also uncovers the lack of existence of cross-conversation between the independentist and unionist political block claimed in other studies.<\/jats:p>","DOI":"10.1007\/s13278-024-01251-8","type":"journal-article","created":{"date-parts":[[2024,4,27]],"date-time":"2024-04-27T07:02:26Z","timestamp":1714201346000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Overview of the Twitter conversation around #14F 2021 Catalonia regional election: an analysis of echo chambers and presence of social bots"],"prefix":"10.1007","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3313-944X","authenticated-orcid":false,"given":"Raul","family":"Broto Cervera","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7534-1326","authenticated-orcid":false,"given":"Cristina","family":"P\u00e9rez-Sol\u00e0","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3185-9101","authenticated-orcid":false,"given":"Albert","family":"Batlle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,4,27]]},"reference":[{"key":"1251_CR1","doi-asserted-by":"crossref","unstructured":"Abilov A, Hua Y, Matatov H, Amir O, Naaman M (2021) VoterFraud2020: a multi-modal dataset of election fraud claims on Twitter. 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