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dc.contributor.author | Lamirán Palomares, José María | es_ES |
dc.contributor.author | Baviera Puig, Tomás | es_ES |
dc.contributor.author | Baviera Puig, Maria Amparo | es_ES |
dc.date.accessioned | 2021-02-25T11:29:07Z | |
dc.date.available | 2019-03-20T12:31:30Z | |
dc.date.available | 2021-02-25T11:29:07Z | |
dc.date.issued | 2019-03-20 | |
dc.identifier.uri | http://hdl.handle.net/10251/118266 | |
dc.description | We analysed 55,572 tweets (English and non-English) sent initially by 20,303 users, which later fell to 20,175 users after we detected 128 errors or duplicates, among other issues. Once the database was refined, we identified the interactions among the users in the conversation through mentions and re-tweets. Although we cannot assure that we have all the tweets specified with that condition (with the hashtag #TWC2016), at least we have a big sample that we consider enough for our research. The hashtag (#TWC2016) was the same as the one used by The Women’s Conference 2016. This Conference was held in December 2016. Though the dates did not coincide, we checked that there was no tweet of this event in our database. | es_ES |
dc.description.abstract | [EN] Social media platforms have had a significant impact on the public image of sports in recent years. Through the relational dynamics of the communication on these networks, many users have emerged whose opinions can exert a great deal of influence on public conversation online. This research aims to identify the influential Twitter users during the 2016 UCI Track Cycling World Championships using different variables which, in turn, represent different dimensions of influence (popularity, activity and authority). Mathematical variables of the social network analysis and variables provided by Twitter and Google are compared. As a result, no single variable assessed is sufficient to identify the different kinds of influential Twitter users. Having a certain type of account is not enough to make a user an influencer if they do not engage (actively or passively) in the conversation. Choosing some influencers or others will depend on the objectives pursued. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Universitat Politècnica de València | |
dc.relation.uri | https://doi.org/10.3390/socsci8050141 | |
dc.relation.uri | https://doi.org/10.3390/socsci9100169 | |
dc.rights | Reconocimiento - No comercial - Compartir igual (by-nc-sa) | es_ES |
dc.subject | es_ES | |
dc.subject | Influence | es_ES |
dc.subject | Social Network Analysis | es_ES |
dc.subject | Social media | es_ES |
dc.subject | Influencers | es_ES |
dc.subject | Sports | es_ES |
dc.subject | Deportes | es_ES |
dc.subject | Redes sociales | es_ES |
dc.subject | Influencia | es_ES |
dc.subject | Análisis de redes sociales | es_ES |
dc.subject.classification | COMERCIALIZACION E INVESTIGACION DE MERCADOS | es_ES |
dc.subject.classification | ECONOMIA, SOCIOLOGIA Y POLITICA AGRARIA | es_ES |
dc.title | Dataset Twitter - 2016 UCI Track Cycling World Championships | es_ES |
dc.type | Dataset | es_ES |
dc.identifier.doi | 10.4995/Dataset/10251/118266 | |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Economía y Ciencias Sociales - Departament d'Economia i Ciències Socials | es_ES |
dc.description.bibliographicCitation | Lamirán Palomares, JM.; Baviera Puig, T.; Baviera Puig, MA. (2019). Dataset Twitter - 2016 UCI Track Cycling World Championships. https://doi.org/10.4995/Dataset/10251/118266 | es_ES |
dc.type.version | info:eu-repo/semantics/submittedVersion | es_ES |