Abstract
Social networks have transformed the conception of the television audience. In order to adapt to a viewer increasingly active on the Internet, televisions conducted social media strategies to generate interactivity and attract users to their social profiles. One of them is based on the live-tweeting phenomenon, in which the conversation is encouraged through publications on Twitter during the broadcast of the programme. This research analyses the effectiveness of live-tweeting as a strategy for promoting user traffic on social networks and its impact in the social audience. According to a quantitative methodology, we have selected four Spanish prime time programmes broadcasted during the first half of September 2016. The aim is to study the network of interactions generated around the programme during its broadcast and the degree of influence of the official profiles in each case.
S. Direito-Rebollal—Beneficiary of the Faculty Training Program funded by the Ministry of Education, Culture and Sport (Government of Spain).
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Acknowledgments
The results of this article are part of the R+D research project “Indicators related to broadcasters’ governance, funding, accountability, innovation, quality and public service applicable to Spain in the digital context” (Reference: CSO2015-66543-P) and “Informational uses and preferences in the new media landscape in Spain: journalism models for mobile devices” (Reference: CSO2015-64662-C4-4-R), funded by the Spanish Ministry of Economy and Competitiveness, as well as the activities promoted by the International Research Network Communication Management (R2016/019 XESCOM) supported by the Department of Culture, Education and University Management of the Government of Galicia.
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Direito-Rebollal, S., Lago-Vázquez, D., Rodríguez-Vázquez, AI. (2017). Television and Social Networks: An Analysis of the Influence of Live-Tweeting in the Social Audiences. In: Rocha, Á., Correia, A., Adeli, H., Reis, L., Costanzo, S. (eds) Recent Advances in Information Systems and Technologies. WorldCIST 2017. Advances in Intelligent Systems and Computing, vol 571. Springer, Cham. https://doi.org/10.1007/978-3-319-56541-5_13
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