Quantifying the Economic and Cultural Biases of Social Media through Trending Topics

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dc.contributor.author Carrascosa, Juan Miguel
dc.contributor.author Cuevas, Rubén
dc.contributor.author González, Roberto
dc.contributor.author Azcorra, Arturo
dc.contributor.author García, David
dc.date.accessioned 2015-09-10T09:56:35Z
dc.date.available 2015-09-10T09:56:35Z
dc.date.issued 2015-07
dc.identifier.bibliographicCitation PLoS ONE (2015). 10(7), e0134407.
dc.identifier.issn 1932-6203
dc.identifier.uri http://hdl.handle.net/10016/21541
dc.description Data are publicly available at: Carrascosa, J and Cuevas, R and Gonzalez, R and Azcorra, A and Garcia, D. Dataset—Quantifying the Economic and Cultural Biases of Social Media through Trending Topics. http://dx.doi.org/10.6084/m9.figshare.1381869
dc.description.abstract Online social media has recently irrupted as the last major venue for the propagation of news and cultural content, competing with traditional mass media and allowing citizens to access new sources of information. In this paper, we study collectively filtered news and popular content in Twitter, known as Trending Topics (TTs), to quantify the extent to which they show similar biases known for mass media. We use two datasets collected in 2013 and 2014, including more than 300.000 TTs from 62 countries. The existing patterns of leader-follower relationships among countries reveal systemic biases known for mass media: Countries concentrate their attention to small groups of other countries, generating a pattern of centralization in which TTs follow the gradient of wealth across countries. At the same time, we find subjective biases within language communities linked to the cultural similarity of countries, in which countries with closer cultures and shared languages tend to follow each other's TTs. Moreover, using a novel methodology based on the Google News service, we study the influence of mass media in TTs for four countries. We find that roughly half of the TTs in Twitter overlap with news reported by mass media, and that the rest of TTs are more likely to spread internationally within Twitter. Our results confirm that online social media have the power to independently spread content beyond mass media, but at the same time social media content follows economic incentives and is subject to cultural factors and language barriers.
dc.description.sponsorship DG acknowledges funding from the SNSF project CR21I1_146499. JMC and RC acknowledge funding from the European Union’s FP7 program under the project eCOUSIN (318398) and the EUH2020 ReCRED project (653417). RG acknowledge funding from the European Union’s FP7 program under the project METRICS (607728). AA and RC acknowledge funding from the Regional Government of Madrid under the MEDIANET Project (S2009/TIC-1468) and BRADE project (P2013/ICE-2958).
dc.format.extent 14
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher PLOS (Public Library of Science)
dc.rights Atribución 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by/3.0/es/
dc.subject.other Mass media
dc.subject.other Twitter
dc.subject.other Social Media
dc.subject.other Social Communication
dc.subject.other Cultural Bias
dc.subject.other Economics
dc.subject.other Trending Topic
dc.title Quantifying the Economic and Cultural Biases of Social Media through Trending Topics
dc.type article
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1371/journal.pone.0134407
dc.subject.eciencia Telecomunicaciones
dc.identifier.doi 10.1371/journal.pone.0134407
dc.rights.accessRights openAccess
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/318398
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/607728
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/653417/EU/ReCRED
dc.relation.projectID Comunidad de Madrid. S2009/TIC-1468/MEDIANET
dc.relation.projectID Comunidad de Madrid. S2013/ICE-2958/BRADE-CM
dc.type.version publishedVersion
dc.identifier.publicationfirstpage 1
dc.identifier.publicationissue 7
dc.identifier.publicationlastpage 14
dc.identifier.publicationtitle PLoS ONE
dc.identifier.publicationvolume 10
dc.identifier.uxxi AR/0000017166
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