Identifying Opinion Leaders on Twitter during Sporting Events: Lessons from a Case Study

[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. First, we calculated the Spearman¿s rank correlation coefficient among all users (n = 20,175) in pairwise comparisons. Next, we performed a qualitative analysis of the top 25 influential users ranked by each variable. As a result, no single variable assessed is sufficient to identify the different kinds of influential Twitter users. The reason that some variables vary so greatly is that the components of influence are very different. Influence is a contextualised phenomenon. 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 the influencers will depend on the objectives pursued.Lamirán-Palomares, JM.; Baviera, T.; Baviera-Puig, A. (2019). Identifying Opinion Leaders on Twitter during Sporting Events: Lessons from a Case Study. Social Sciences. 8(5):1-18. https://doi.org/10.3390/socsci8050141S11885Abeza, G., Pegoraro, A., Naraine, M. L., Séguin, B., O’, N., & Reilly, N. A. (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(3/4), 184. doi:10.1504/ijsmm.2014.072010Agre, P. E. (2002). Real-Time Politics: The Internet and the Political Process. The Information Society, 18(5), 311-331. doi:10.1080/01972240290075174Anagnostopoulos, C., Parganas, P., Chadwick, S., & Fenton, A. (2018). Branding in pictures: using Instagram as a brand management tool in professional team sport organisations. European Sport Management Quarterly, 18(4), 413-438. doi:10.1080/16184742.2017.1410202Barabási, A.-L., & Albert, R. (1999). Emergence of Scaling in Random Networks. Science, 286(5439), 509-512. doi:10.1126/science.286.5439.509Barnes, J. A., & Harary, F. (1983). Graph theory in network analysis. Social Networks, 5(2), 235-244. doi:10.1016/0378-8733(83)90026-6Bonacich, P. (1972). Factoring and weighting approaches to status scores and clique identification. The Journal of Mathematical Sociology, 2(1), 113-120. doi:10.1080/0022250x.1972.9989806Borgatti, S. P., & Everett, M. G. (2006). A Graph-theoretic perspective on centrality. Social Networks, 28(4), 466-484. doi:10.1016/j.socnet.2005.11.005Bouguessa, M., & Romdhane, L. B. (2015). Identifying Authorities in Online Communities. ACM Transactions on Intelligent Systems and Technology, 6(3), 1-23. doi:10.1145/2700481BROSIUS, H.-B., & WEIMANN, G. (1996). Who Sets the Agenda. Communication Research, 23(5), 561-580. doi:10.1177/009365096023005002Carter, D. (2016). Hustle and Brand: The Sociotechnical Shaping of Influence. Social Media + Society, 2(3), 205630511666630. doi:10.1177/2056305116666305Chew, S., Metheney, E., & Teague, T. (2017). Modelling and Simulation of the Formation of Social Networks. Social Sciences, 6(3), 79. doi:10.3390/socsci6030079Clavio, G., Burch, L. M., & Frederick, E. L. (2012). Networked Fandom: Applying Systems Theory to Sport Twitter Analysis. International Journal of Sport Communication, 5(4), 522-538. doi:10.1123/ijsc.5.4.522Cleland, J. (2013). Racism, Football Fans, and Online Message Boards. Journal of Sport and Social Issues, 38(5), 415-431. doi:10.1177/0193723513499922Dahlgren, P. (2005). The Internet, Public Spheres, and Political Communication: Dispersion and Deliberation. Political Communication, 22(2), 147-162. doi:10.1080/10584600590933160Dart, J. (2012). New Media, Professional Sport and Political Economy. Journal of Sport and Social Issues, 38(6), 528-547. doi:10.1177/0193723512467356Campo-Ávila, J. del, Moreno-Vergara, N., & Trella-López, M. (2013). Bridging the Gap Between the Least and the Most Influential Twitter Users. Procedia Computer Science, 19, 437-444. doi:10.1016/j.procs.2013.06.059Delia, E. B., & Armstrong, C. G. (2015). #Sponsoring the #FrenchOpen: An Examination of Social Media Buzz and Sentiment. Journal of Sport Management, 29(2), 184-199. doi:10.1123/jsm.2013-0257Demir, R., & Söderman, S. (2015). Strategic sponsoring in professional sport: a review and conceptualization. European Sport Management Quarterly, 15(3), 271-300. doi:10.1080/16184742.2015.1042000Dubois, E., & Gaffney, D. (2014). The Multiple Facets of Influence. American Behavioral Scientist, 58(10), 1260-1277. doi:10.1177/0002764214527088Filo, K., Lock, D., & Karg, A. (2015). Sport and social media research: A review. Sport Management Review, 18(2), 166-181. doi:10.1016/j.smr.2014.11.001Freberg, K., Graham, K., McGaughey, K., & Freberg, L. A. (2011). Who are the social media influencers? A study of public perceptions of personality. Public Relations Review, 37(1), 90-92. doi:10.1016/j.pubrev.2010.11.001Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social Networks, 1(3), 215-239. doi:10.1016/0378-8733(78)90021-7Freeman, L. C., Borgatti, S. P., & White, D. R. (1991). Centrality in valued graphs: A measure of betweenness based on network flow. Social Networks, 13(2), 141-154. doi:10.1016/0378-8733(91)90017-nGayo-Avello, D. (2013). Nepotistic relationships in Twitter and their impact on rank prestige algorithms. Information Processing & Management, 49(6), 1250-1280. doi:10.1016/j.ipm.2013.06.003Gibbs, C., O’Reilly, N., & Brunette, M. (2014). Professional Team Sport and Twitter: Gratifications Sought and Obtained by Followers. International Journal of Sport Communication, 7(2), 188-213. doi:10.1123/ijsc.2014-0005Hambrick, M. E. (2012). Six Degrees of Information: Using Social Network Analysis to Explore the Spread of Information Within Sport Social Networks. International Journal of Sport Communication, 5(1), 16-34. doi:10.1123/ijsc.5.1.16Hambrick, M. E., & Mahoney, T. Q. (2011). «It»s incredible trust me’: exploring the role of celebrity athletes as marketers in online social networks. International Journal of Sport Management and Marketing, 10(3/4), 161. doi:10.1504/ijsmm.2011.044794Hambrick, M. E., & Pegoraro, A. (2014). Social Sochi: using social network analysis to investigate electronic word-of-mouth transmitted through social media communities. International Journal of Sport Management and Marketing, 15(3/4), 120. doi:10.1504/ijsmm.2014.072005Hambrick, M. E., & Sanderson, J. (2013). Gaining Primacy in the Digital Network: Using Social Network Analysis to Examine Sports Journalists’ Coverage of the Penn State Football Scandal via Twitter. Journal of Sports Media, 8(1), 1-18. doi:10.1353/jsm.2013.0003Hambrick, M. E., Simmons, J. M., Greenhalgh, G. P., & Greenwell, T. C. (2010). Understanding Professional Athletes’ Use of Twitter: A Content Analysis of Athlete Tweets. International Journal of Sport Communication, 3(4), 454-471. doi:10.1123/ijsc.3.4.454Hofer, M., & Aubert, V. (2013). Perceived bridging and bonding social capital on Twitter: Differentiating between followers and followees. Computers in Human Behavior, 29(6), 2134-2142. doi:10.1016/j.chb.2013.04.038Hull, K., & Schmittel, A. (2014). A Fumbled Opportunity? A Case Study of Twitter’s Role in Concussion Awareness Opportunities During the Super Bowl. Journal of Sport and Social Issues, 39(1), 78-94. doi:10.1177/0193723514558928Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53(1), 59-68. doi:10.1016/j.bushor.2009.09.003Kassing, J. W., & Sanderson, J. (2010). Fan–Athlete Interaction and Twitter Tweeting Through the Giro: A Case Study. International Journal of Sport Communication, 3(1), 113-128. doi:10.1123/ijsc.3.1.113Katz, E. (1957). The Two-Step Flow of Communication: An Up-To-Date Report on an Hypothesis. Public Opinion Quarterly, 21(1, Anniversary Issue Devoted to Twenty Years of Public Opinion Research), 61. doi:10.1086/266687Khan, H. U., Daud, A., Ishfaq, U., Amjad, T., Aljohani, N., Abbasi, R. A., & Alowibdi, J. S. (2017). Modelling to identify influential bloggers in the blogosphere: A survey. Computers in Human Behavior, 68, 64-82. doi:10.1016/j.chb.2016.11.012Koenig-Lewis, N., Asaad, Y., & Palmer, A. (2017). Sports events and interaction among spectators: examining antecedents of spectators’ value creation. European Sport Management Quarterly, 18(2), 193-215. doi:10.1080/16184742.2017.1361459Kolyperas, D., Maglaras, G., & Sparks, L. (2018). Sport fans’ roles in value co-creation. European Sport Management Quarterly, 19(2), 201-220. doi:10.1080/16184742.2018.1505925Kunkel, T., Walker, M., & Hodge, C. M. (2018). The influence of advertising appeals on consumer perceptions of athlete endorser brand image. European Sport Management Quarterly, 19(3), 373-395. doi:10.1080/16184742.2018.1530688Lahuerta-Otero, E., & Cordero-Gutiérrez, R. (2016). Looking for the perfect tweet. The use of data mining techniques to find influencers on twitter. Computers in Human Behavior, 64, 575-583. doi:10.1016/j.chb.2016.07.035Lewin, K. (1939). Field Theory and Experiment in Social Psychology: Concepts and Methods. American Journal of Sociology, 44(6), 868-896. doi:10.1086/218177McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a Feather: Homophily in Social Networks. Annual Review of Sociology, 27(1), 415-444. doi:10.1146/annurev.soc.27.1.415Meenaghan, T., McLoughlin, D., & McCormack, A. (2013). New Challenges in Sponsorship Evaluation Actors, New Media, and the Context of Praxis. Psychology & Marketing, 30(5), 444-460. doi:10.1002/mar.20618Misener, L., & Mason, D. S. (2006). Creating community networks: Can sporting events offer meaningful sources of social capital? Managing Leisure, 11(1), 39-56. doi:10.1080/13606710500445676Morone, F., & Makse, H. A. (2015). Influence maximization in complex networks through optimal percolation. Nature, 524(7563), 65-68. doi:10.1038/nature14604Naraine, M. L., & Parent, M. M. (2016). Illuminating Centralized Users in the Social Media Ego Network of Two National Sport Organizations. Journal of Sport Management, 30(6), 689-701. doi:10.1123/jsm.2016-0067Naraine, M. L., Schenk, J., & Parent, M. M. (2016). Coordination in International and Domestic Sports Events: Examining Stakeholder Network Governance. Journal of Sport Management, 30(5), 521-537. doi:10.1123/jsm.2015-0273Norris, P., & Curtice, J. (2008). Getting the Message Out: A Two-Step Model of the Role of the Internet in Campaign Communication Flows During the 2005 British General Election. Journal of Information Technology & Politics, 4(4), 3-13. doi:10.1080/19331680801975359Pegoraro, A. (2010). Look Who’s Talking—Athletes on Twitter: A Case Study. International Journal of Sport Communication, 3(4), 501-514. doi:10.1123/ijsc.3.4.501Perić, M. (2018). Estimating the Perceived Socio-Economic Impacts of Hosting Large-Scale Sport Tourism Events. Social Sciences, 7(10), 176. doi:10.3390/socsci7100176Quatman, C., & Chelladurai, P. (2008). Social Network Theory and Analysis: A Complementary Lens for Inquiry. Journal of Sport Management, 22(3), 338-360. doi:10.1123/jsm.22.3.338Quatman, C., & Chelladurai, P. (2008). The Social Construction of Knowledge in the Field of Sport Management: A Social Network Perspective. Journal of Sport Management, 22(6), 651-676. doi:10.1123/jsm.22.6.651Riquelme, F., & González-Cantergiani, P. (2016). Measuring user influence on Twitter: A survey. Information Processing & Management, 52(5), 949-975. doi:10.1016/j.ipm.2016.04.003Santomier, J. (2008). New media, branding and global sports sponsorship. International Journal of Sports Marketing and Sponsorship, 10(1), 9-22. doi:10.1108/ijsms-10-01-2008-b005Small, T. A. (2011). WHAT THE HASHTAG? Information, Communication & Society, 14(6), 872-895. doi:10.1080/1369118x.2011.554572Towner, T., & Lego Munoz, C. (2016). Boomers versus Millennials: Online Media Influence on Media Performance and Candidate Evaluations. Social Sciences, 5(4), 56. doi:10.3390/socsci5040056Veglis, A., & Maniou, T. A. (2018). The Mediated Data Model of Communication Flow: Big Data and Data Journalism. KOME, 6(2), 32-43. doi:10.17646/kome.2018.23Wäsche, H. (2015). Interorganizational cooperation in sport tourism: A social network analysis. Sport Management Review, 18(4), 542-554. doi:10.1016/j.smr.2015.01.003Wäsche, H., Dickson, G., Woll, A., & Brandes, U. (2017). Social network analysis in sport research: an emerging paradigm. European Journal for Sport and Society, 14(2), 138-165. doi:10.1080/16138171.2017.1318198Yan, G., Pegoraro, A., & Watanabe, N. M. (2018). Student-Athletes’ Organization of Activism at the University of Missouri: Resource Mobilization on Twitter. Journal of Sport Management, 32(1), 24-37. doi:10.1123/jsm.2017-0031Yan, G., Watanabe, N. M., Shapiro, S. L., Naraine, M. L., & Hull, K. (2018). Unfolding the Twitter scene of the 2017 UEFA Champions League Final: social media networks and power dynamics. European Sport Management Quarterly, 19(4), 419-436. doi:10.1080/16184742.2018.1517272Yu, Y., & Wang, X. (2015). World Cup 2014 in the Twitter World: A big data analysis of sentiments in U.S. sports fans’ tweets. Computers in Human Behavior, 48, 392-400. doi:10.1016/j.chb.2015.01.07

Gain-Reconfigurable Hybrid Metal-Graphene Printed Yagi Antenna for Energy Harvesting Applications

This paper presents a hybrid metal-graphene printed Yagi antenna with reconfigurable gain that operates in the 5.5-GHz band. The balun and the driven elements are made of copper, while the directors are made of graphene. The graphene acts as a tunable material in the design. By switching the conductivity of the graphene, it is achieved a similar effect to adding or subtracting directors in the antenna. Hence the gain of the printed Yagi can be easily controlled. This could be of special interest in RF energy harvesting in the design of reconfigurable harvesting elements.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Eficiencia técnica en el sector oleícola. Un nuevo método con factores ambientales

En este trabajo analizamos la eficiencia considerando variables de entorno en el ámbito del sector oleícola de Andalucía. Se implementa un nuevo método con dos variables, como una ampliación del planteado en una publicación anterior por Dios-Palomares et al. Posteriormente se investiga sobre los posibles factores que influyen en la eficiencia con el fin de establecer perfiles y plantear estrategias de mejora. La eficiencia media encontrada es del 57%, siendo la pura del 70% y la de escala del 84%. En cuanto a la determinación de perfiles asociados con el nivel de eficiencia, podemos concluir que no se ha encontrado relación entre los niveles de eficiencia y las variables socioeconómicas como edad, antigüedad, y tecnologías de Internet. Sin embargo, son más eficientes las almazaras que se asocian para comercializar, así como las que realizan doble extracción y las que están situadas fuera del casco urbano.Eficiencia, Variables ambientales, almazaras

Analytical Approach of Director Tilting in Nematic Liquid Crystals for Electronically Tunable Devices

This paper presents an analytical expression that models the tilt angle of directors in a nematic liquid crystal (LC), depending on its elastic properties, its dielectric anisotropy, and the quasi-static electric field applied. The analytical solution obtained is fast and easily computable in comparison with numerical estimations and is of special interest in radiofrequency; for instance, for the LC modeling in full-wave electromagnetic simulators in the design process of electronically tunable devices, such as microwave phase shifters or electronically steerable antennas for satellite communications. Subsequently, a comparison is made between numerical approaches (self-implemented shooting method) and the analytical formulas when varying the parameters of the LC, being demonstrated its usefulness. The average LC director is then obtained and used to form the full permittivity tensor that completely characterizes the electrical properties of the material. Finally, an electromagnetic simulation is carried out to show the capabilities of the LC as a tunable phase shifter. It is shown that only 5 cm of a commercial 200-mm LC mixture is necessary to achieve 360 of the maximum variable phase shift at the 30-GHz bandThis work was supported in part by the Spanish Research and Development National Program under Project TIN2016-75097-P, and in part by the Ministerio de Economía under Project TEC2017-85529-C3-1-R

Improving the accuracy while preserving the interpretability of fuzzy function approximators by means of multi-objective evolutionary algorithms

AbstractThe identification of a model is one of the key issues in the field of fuzzy system modeling and function approximation theory. An important characteristic that distinguishes fuzzy systems from other techniques in this area is their transparency and interpretability. Especially in the construction of a fuzzy system from a set of given training examples, little attention has been paid to the analysis of the trade-off between complexity and accuracy maintaining the interpretability of the final fuzzy system. In this paper a multi-objective evolutionary approach is proposed to determine a Pareto-optimum set of fuzzy systems with different compromises between their accuracy and complexity. In particular, two fundamental and competing objectives concerning fuzzy system modeling are addressed: fuzzy rule parameter optimization and the identification of system structure (i.e. the number of membership functions and fuzzy rules), taking always in mind the transparency of the obtained system. Another key aspect of the algorithm presented in this work is the use of some new expert evolutionary operators, specifically designed for the problem of fuzzy function approximation, that try to avoid the generation of worse solutions in order to accelerate the convergence of the algorithm

The Symbiosis Interactome: a computational approach reveals novel components, functional interactions and modules in Sinorhizobium meliloti

<p>Abstract</p> <p>Background</p> <p><it>Rhizobium</it>-Legume symbiosis is an attractive biological process that has been studied for decades because of its importance in agriculture. However, this system has undergone extensive study and although many of the major factors underpinning the process have been discovered using traditional methods, much remains to be discovered.</p> <p>Results</p> <p>Here we present an analysis of the 'Symbiosis Interactome' using novel computational methods in order to address the complex dynamic interactions between proteins involved in the symbiosis of the model bacteria <it>Sinorhizobium meliloti </it>with its plant hosts. Our study constitutes the first large-scale analysis attempting to reconstruct this complex biological process, and to identify novel proteins involved in establishing symbiosis. We identified 263 novel proteins potentially associated with the Symbiosis Interactome. The topology of the Symbiosis Interactome was used to guide experimental techniques attempting to validate novel proteins involved in different stages of symbiosis. The contribution of a set of novel proteins was tested analyzing the symbiotic properties of several <it>S. meliloti </it>mutants. We found mutants with altered symbiotic phenotypes suggesting novel proteins that provide key complementary roles for symbiosis.</p> <p>Conclusion</p> <p>Our 'systems-based model' represents a novel framework for studying host-microbe interactions, provides a theoretical basis for further experimental validations, and can also be applied to the study of other complex processes such as diseases.</p

The role of the oxide shell in the chemical functionalization of plasmonic gallium nanoparticles

S. Catalán-Gómez, M. Briones, A. Redondo-Cubero, F. J. Palomares, F. Nucciarelli, E. Lorenzo, J. L. Pau, "The role of the oxide shell in the chemical functionalization of plasmonic gallium nanoparticles", SPIE Optics + Optoelectronics Proc. SPIE 10231 (16 May 2017); doi: 10.1117/12.2265665; Copyright 2017 Society of Photo‑Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.Plasmonic Ga nanoparticles (NPs) were thermally oxidized at low temperature in order to increase the native Ga 2 O 3 shell thickness and to improve their stability during the chemical functionalization. The optical, structural and chemical properties of the oxidized NPs have been studied by spectroscopic ellipsometry, scanning electron microscopy, grazing incidence X-ray diffraction and X-ray photoelectron spectroscopy. A clear redshift of the peak wavelength is observed with the increasing annealing time due to the Ga 2 O 3 thickness increase, and barely affecting the intensity of the plasmon resonance. This oxide layer enhances the stability of the NPs upon immersion in ethanol or water. The surface sensitivity properties of the as-grown and oxidized NPs were investigated by linking a thiol group from 6-Mercapto-1-hexanol through immersion. Ellipsometric spectra at the reversal polarization handedness (RPH) condition are in agreement with the Langmuir absorption model, indicating the formation of a thiol monolayer on the NPs

Bovine Tuberculosis in a Free Ranging Red Fox (Vulpes vulpes) from Doñana National Park (Spain)

During 1997 and 1998, a survey of Iberian carnivores was conducted to study the epidemiology of bovine tuberculosis in the Doñana National Park and surrounding areas in southwestern Spain. Post-mortem examinations were done on seven red foxes (Vulpes vulpes), two Egyptian mongoose (Herpestes ichneumon), one weasel (Mustela nivalis), two genets (Genetta genetta), one Iberian lynx (Lynx pardinus), one Eurasian badger (Meles meles), and two polecats (Mustela putorius). Lesions suggestive of bovine tuberculosis were not detected but, in culture, Mycobacterium bovis was isolated from the retropharyngeal lymph nodes of one adult male red fox. This is the first report of M. bovis infection in red fox in Spain.Peer reviewe

Aplicación de PCA y técnicas bayesianas a la clasificación de píxeles basada en color

En este trabajo se propone un método para la clasificación de píxeles en base a su color. A partir de un conjunto de variables que caracterizan un píxel según su color se determinará cuáles de éstas son las más representativas y se realizará la clasificación propiamente dicha. Para ello nuestro método consta de dos fases: en la primera se aplica PCA para obtener el conjunto de variables características más informativas; en la segunda, dichas variables se utilizan como patrones de las clases de un clasificador bayesiano. El método se ilustra a través de varios experimentos