Propuesta de índice de influencia de contenidos (Influ@RT) en Twitter

G. Figuerola, Carlos and Alonso-Berrocal, José-Luis and Zazo-Rodríguez, Ángel-F. Propuesta de índice de influencia de contenidos (Influ@RT) en Twitter. Scire. Representación y Organización del Conocimiento, 2015, vol. 21, n. 1, pp. 21-26. [Journal article (Paginated)]

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English abstract

Twitter is one of the most popular social networks and the one with the highest increase in its number of users in the last years. Measuring the influence that the information transmitted through the tweets have had in its environment is key to define the importance of the profile that generates them and the audience they can reach. We propose a new index, Influ@RT, which considers several categories of data to deter- mine the scope and influence that their profiles have in the particular field to whom they belong. Their cal- culation was applied to a field formed by the profiles that the Spanish university libraries have in this net- work. Several APIs were used for data collection that are described. The obtained results point to a better definition of the level of influence by the proposed index.

Spanish abstract

Twitter es una de las redes sociales más conocidas y que han tenido un mayor incremento en su número de usuarios en los últimos años. Poder medir la in- fluen-cia que la información transmitida por medio de los tweets tiene en su entorno permite definir la im- por-tancia del perfil que la genera y su audiencia potencial. Proponemos un nuevo índice, Influ@RT, que considera varias categorías de datos y que per- mite determinar la influencia y el alcance que tienen en un determinado ámbito los perfiles que a él perte- necen. Su cálculo se aplicó sobre el ámbito que for- man los perfiles que poseen las bibliotecas univer- sitarias españolas en esta red. Se describen las APIs empleadas para la recogida de datos. Los resultados obtenidos apuntan a que el índice propuesto consi- gue una mejor definición del nivel de influencia.

Item type: Journal article (Paginated)
Keywords: Twitter. Influ@RT. Informetría. Redes sociales. Influencia del contenido. Índices de influencia.
Subjects: B. Information use and sociology of information > BA. Use and impact of information.
H. Information sources, supports, channels. > HT. Web 2.0, Social networks
Depositing user: Carlos G. Figuerola
Date deposited: 17 May 2016 11:21
Last modified: 17 May 2016 11:21
URI: http://hdl.handle.net/10760/29271

References

Alonso Berrocal, J. L.; Figuerola, C. G.; Zazo Rodríguez, Á. (2013). REINA at RepLab2013 Topic Detection Task: Community Detection. // Working Notes for the CLEF 2013 Evaluation Labs and Workshop, Valencia, Spain, 23-26 September, 2013.

Alonso Berrocal, J. L.; Gómez Díaz, R.; Figuerola, C. G.; Zazo Rodríguez, Á. F.; Cordón García, J. A. (2012). Propuesta de estudio del campo semántico de los libros electrónicos en Twitter. // Scire. 18:2, 87-97.

Berry, M. (2010). Better Know the Klout Classes. // Measuring Online Influence: The Official Klout Blog. 2. http://corp.klout.com/blog/2010/08/better-know-the-klout-classes

Boyd, D.; Golder, S.; Lotan, G. (2010). Tweet, tweet, retweet: Conversational aspects of retweeting on twitter. // / 43rd Hawaii International Conference on System Sciences (HICSS), 2010.

Cha, M.; Benevenuto, F.; Haddadi, H.; Gummadi, K. (2012). The world of connections and information flow in Twitter. // IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans. 42:4, 991-998.

Chamberlin, L.; Lehmann, K. (2011). Twitter in higher education. // Cutting-edge Technologies in Higher Education. 1, 375-391.

Chen, S.-C.; Yen, D. C.; Hwang, M. I. (2012). Factors influencing the continuance intention to the usage of Web 2.0: An empirical study. // Computers in Human Behavior. 28(3), 933-941.

Dabbagh, N.; Kitsantas, A. (2012). Personal Learning Environments, social media, and self-regulated learning: A natural formula for connecting formal and informal learning. // The Internet and higher education. 15:1, 3-8.

Ebner, M.; Lienhardt, C.; Rohs, M.; Meyer, I. (2010). Microblogs in Higher Education–A chance to facilitate informal and process-oriented learning? // Computers & Education. 55:1, 92-100.

Edwards, C.; Spence, P. R.; Gentile, C. J.; Edwards, A.; Edwards, A. (2013). How much Klout do you have... A test of system generated cues on source credibility. // Computers in Human Behavior. 29, A12-A16.

Garcia Esparza, S.; O’Mahony, M. P.; Smyth, B. (2012). Mining the real-time web: a novel approach to product recommendation. // Knowledge-Based Systems. 29, 3-11.

Guzmán Duque, A. P.; del Moral Pérez, M. E.; Ladrón de Guevara, F. G.; Gil Gómez, H. (2013). Impacto de Twitter en la comunicación y promoción institucional de las universidades. // Pixel-Bit: Revista de Medios y Educacion. 43.

Java, A.; Song, X.; Finin, T.; Tseng, B. (2009). Why we twitter: An analysis of a microblogging community // Advances in Web Mining and Web Usage Analysis. Springer. 118-138.

Lee, K.; Palsetia, D.; Narayanan, R.; Patwary, M. M. A.; Agrawal, A.; Choudhary, A. (2011). Twitter trending topic classification. // IEEE 11th International Conference on Data Mining Workshops (ICDMW), 2011.

Metzger, M. J.; Flanagin, A. J.; Medders, R. B. (2010). Social and heuristic approaches to credibility evaluation online. // Journal of Communication. 60:3, 413-439.

Narr, S.; De Luca, E. W.; Albayrak, S. (2011). Extracting semantic annotations from twitter. // Proceedings of the fourth workshop on Exploiting semantic annotations in information retrieval.

Özsoy, S. (2011). Use of New Media by Turkish Fans in Sport Communication: Facebook and Twitter. // Journal of Human Kinetics. 28:1, 165-176.

Pérez, F. (2013). Rankings ISSUE: indicadores sintéticos de las universidades españolas. DOI: http://dx.doi.org/10.12842/RANKINGS_ISSUE_201

Petrović, S.; Osborne, M.; Lavrenko, V. (2010). Streaming first story detection with application to Twitter. // Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics.

Sankaranarayanan, J.; Samet, H.; Teitler, B. E.; Lieberman, M. D.; Sperling, J. (2009). TwitterStand: news in tweets. // Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems.

Serrano-Puche, J. (2012). Herramientas web para la medición de la influencia digital: análisis de klout y PeerIndex. // El profesional de la información. 21:3, 298-303.

Thelwall, M.; Buckley, K.; Paltoglou, G. (2011). Sentiment in Twitter events. // Journal of the American Society for Information Science and Technology. 62:2, 406-418.

Veletsianos, G. (2012). Higher education scholars' participation and practices on Twitter. // Journal of Computer Assisted Learning. 28:4, 336-349.

Westerman, D.; Spence, P. R.; Van Der Heide, B. (2012). A social network as information: The effect of system generated reports of connectedness on credibility on Twitter. // Computers in Human Behavior. 28:1, 199-206.

Yerva, S. R.; Miklós, Z.; Aberer, K. (2012). Quality-aware similarity assessment for entity matching in Web data. // Information Systems. 37:4, 336-351.


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