This README.txt file was generated on <2021-02-25> by ------------------- GENERAL INFORMATION ------------------- Title of Dataset: Dataset Twitter - 2016 UCI Track Cycling World Championships. Author Information Principal Investigator: Lamirán Palomares, José María. Department of Economics and Social Sciences. Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain. jolapa@doctor.upv.es https://orcid.org/0000-0001-5203-2643 Co-investigator: Tomás Baviera. Department of Economics and Social Sciences. Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain. tobapui@upv.es https://orcid.org/0000-0002-2331-6628 Co-investigator: Amparo Baviera-Puig. Department of Economics and Social Sciences. Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain. ambapui@upv.es https://orcid.org/0000-0002-2258-1155 Date of data collection: <2016-05-23> Geographic location of data collection: Twitter Information about funding sources or sponsorship that supported the collection of the data: No funding. General description: 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. Keywords: Twitter, influence, Social Network Analysis (SNA), social media, influencers, sports, deportes, redes sociales, influencia, análisis de redes sociales. -------------------------- SHARING/ACCESS INFORMATION -------------------------- Open Access to data: Open. Date end Embargo: ---- Licenses/restrictions placed on the data, or limitations of reuse: Reconocimiento - No comercial - Compartir igual (by-nc-sa). Citation for and links to publications that cite or use the data: https://doi.org/10.3390/socsci8050141; https://doi.org/10.3390/socsci9100169 Links/relationships to previous or related data sets: Links to other publicly accessible locations of the data: 10.4995/Dataset/10251/118266 ; http://hdl.handle.net/10251/118266 -------------------- DATA & FILE OVERVIEW -------------------- File list: - “tweet ids - #TWC2016” Relationship between files: there is only 1. Type of version of the dataset: processed data. Total size: 887 KB -------------------------- METHODOLOGICAL INFORMATION -------------------------- Description of methods used for collection/generation of data: From 2 March to 6 March 2016, the UCI Track Cycling World Championships were held in London’s Olympic velodrome at Lee Valley VeloPark. The event’s signage, event programmes and promotional images included various messages inviting spectators—whether live or on television—to interact with the event. These messages included the official hashtag #TWC2016. For our research, we downloaded the tweets with the hashtag #TWC2016 sent from 15 February to 14 March 2016. We included the pre-, during and post periods as cited by Abeza et al. (2014), Yan et al. (2018a) and Yan et al. (2018b). Abeza, Gashaw, Ann Pegoraro, Michael L. Naraine, Benoît Séguin, and Norm O’Reilly. 2014. Activating a global sport sponsorship with social media: an analysis of TOP sponsors, Twitter, and the 2014 Olympic Games. International Journal of Sport Management and Marketing 15: 184–213. https://doi.org/10.1504/IJSMM.2014.072010 Yan, Grace, Ann Pegoraro, and Nicholas M. Watanabe. 2018a. Student-Athletes’ Organization of Activism at the University of Missouri: Resource Mobilization on Twitter. Journal of Sport Management 32: 24–37. https://doi.org/10.1123/jsm.2017-0031 Yan, Grace, Nicholas M. Watanabe, Stephen L. Shapiro, Michael L. Naraine, and Kevin Hull. 2018b. Unfolding the Twitter scene of the 2017 UEFA Champions League Final: social media networks and power dynamics. European Sport Management Quarterly. https://doi.org/10.1080/16184742.2018.1517272 Methods for processing the data: 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. Software- or Instrument-specific information needed to interpret the data, including software and hardware version numbers: - Audiense, specific software for capturing Twitter data. - Excel, to refine the database in order to detect the errors or duplicates. Standards and calibration information, if appropriate: Once the database was refined, we identified the interactions among the users in the conversation through mentions and re-tweets.  Environmental/experimental conditions: 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. Describe any quality-assurance procedures performed on the data: 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. -------------------------- DATA-SPECIFIC INFORMATION -------------------------- Number of variables: 1. Number of cases/rows: 55,572. Variable list, defining any abbreviations, units of measure, codes or symbols used: - “tweetid”: identification number of the tweets downloaded during the research. Missing data codes: 0. Specialized formats or other abbreviations used: none.