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Advanced visualization of Twitter data for its analysis as a communication channel in traditional companies

  • Carmen ZarcoEmail author
  • Elena Santos
  • Oscar Cordón
Regular Paper
  • 5 Downloads

Abstract

The adoption of Twitter as communication channel can provide a significant benefit to firms, allowing them to improve their reputation and check its consistency with their mission and goals, monitor how customers respond to a business decision, and achieve product awareness. However, Twitter engagement is difficult for many companies due to the large amount of human and financial resources required. The aim of this contribution is to identify the situation of Twitter adoption by those kinds of traditional companies, aiming to discern the communication strategies applied from a global and relational view, analyzing the common and differential characteristics. To do so, we propose a methodology based on the use of Twitter data related to presence and impact as well as advanced visualization methods based on social network analysis techniques. It will allow us to obtain visual representations (maps) of the similarity relations with respect to the positioning of the different companies on Twitter. The nature of the brand communication model developed can be established considering the distribution and spatial location of each company on the map. Therefore, the generated maps become technological watch tools allowing a specific company to develop competitive analysis with respect to competitors. We validate our proposal on a specific market, comprised by the wineries holding the Qualified Denomination of Origin Rioja in Spain. These firms have a great sense of tradition, making them reluctant to use technology-based marketing strategies even if wine consumers are highly active users on Twitter.

Keywords

Twitter Communication Information visualization Social network analysis Wineries Denomination of qualified origin rioja 

Notes

References

  1. 1.
    Nelson-Field, K., Riebe, E., Sharp, B.: What’s not to “like?”: Can a Facebook fan base give a brand the advertising reach it needs? J. Advert. Res. 2(52), 262–269 (2012)Google Scholar
  2. 2.
    Smith, K.: Brandwatch (2017). [Online]. https://www.brandwatch.com. Accessed 4 Oct 2018
  3. 3.
    Ferguson, R.: Word of mouth and viral marketing: taking the temperature of the hottest trends in marketing. J. Consum. Mark. 25(3), 179–182 (2008)Google Scholar
  4. 4.
    Xun, J., Guo, B.: Twitter as customer’s eWOM: an empirical study on their impact on firm financial performance. Internet Res. 27(5), 1014–1038 (2017)Google Scholar
  5. 5.
    Percastre-Mendizábal, S., Pont-Sorribes, C., Codina, L.: Propuesta de diseño muestral para el análisis de Twitter en comunicación política. El Profesional de la Información 26(4), 579–588 (2017)Google Scholar
  6. 6.
    Twitter, Twitter (2017). [Online]. http://www.twitter.com. Accessed 2 Oct 2018
  7. 7.
    Laylavi, F., Rajabifard, A., Kalantari, M.: Event relatedness assessment of Twitter messages for emergency response. Inf. Process. Manag. 53(1), 266–280 (2017)Google Scholar
  8. 8.
    Gonzalez-Paule, J., Sun, Y., Moshfeghi, Y.: On fine-grained geolocalisation of tweets and real-time traffic incident detection. Inf. Process. Manag. 56(3), 1119–1132 (2019)Google Scholar
  9. 9.
    Murakami, D., Peters, G., Yamagata, Y., Matsui, T.: Participatory sensing data tweets for micro-urban real-time resiliency monitoring and risk management. IEEE Access 4, 347–372 (2016)Google Scholar
  10. 10.
    Kietzmann, J., Hermkens, K., McCarthy, I., Silvestre, B.: Social media? Get serious! Understanding the functional building blocks of social media. Bus. Horiz. 54(3), 241–251 (2011)Google Scholar
  11. 11.
    Buelarca, M., Buelarca, S.: Twitter: a viable marketing tool for SMEs? Global Bus. Manag. Res. 2(4), 296–309 (2010)Google Scholar
  12. 12.
    Gálvez-Rodríguez, M., Caba-Pérez, C., López-Godoy, M.: Drivers of Twitter as a strategic communication tool for non-profit organizations. Internet Res. 26(5), 1052–1071 (2016)Google Scholar
  13. 13.
    Okazaki, S., Díaz-Martín, A., Rozano, M., Menéndez-Benito, H.D.: Using Twitter to engage with customers: a data mining approach. Internet Res. 25(3), 416–434 (2015)Google Scholar
  14. 14.
    Wasserman, S., Faust, K.: Social Network Analysis: Methods And Applications (Structural Analysis in the Social Sciences). Cambridge University Press, Cambridge (1994)zbMATHGoogle Scholar
  15. 15.
    Barber, N., Dodd, T., Ghiselli, R.: Capturing the younger wine consumer. J. Wine Res. 19(2), 123–141 (2008)Google Scholar
  16. 16.
    Stelzner, M.: Social media marketing industry report. Social media examiner, pp 1–52 (2014). https://www.socialmediaexaminer.com/social-media-marketing-industry-report-2014/
  17. 17.
    Bruwer, J., Wood, G.: The Australian online wine buying consumer: motivation and behaviour perspectives. J. Wine Res. 6(3), 193–211 (2005)Google Scholar
  18. 18.
    Vinography: Social media and the wine industry: a new era. 2014 Septiembre 2012 [Online]. http://www.vinography.com/archives/2012/02/social_media_and_the_wine_indu.html. Accessed Oct 2018
  19. 19.
    Wilson, D., Quinton, S.: Let’s talk about wine: does Twitter have value? Int. J. Wine Bus. Res. 24(4), 271–286 (2012)Google Scholar
  20. 20.
    Alonso, A., Bressan, A., O’Shea, M., Krajsic, V.: Website and social media usage: developments of wine Tourison, hospitality and the wine sector. Tour. Plan. Dev. 25(3), 229–248 (2013)Google Scholar
  21. 21.
    Thelwall, M., Buckley, K., Paltoglou, G.: Sentiment in Twitter events. J. Assoc. Inf. Sci. Technol. 62(2), 406–418 (2011)Google Scholar
  22. 22.
    Rodríguez, H., Restrepo, B., Fernando, L.: Conocimientos y uso del twitter por parte de estudiantes de educación superior. Sophia 11(1), 44–52 (2015)Google Scholar
  23. 23.
    Lin, M., Hoffman, E., Borengasser, C.: Is social media too social for class? a case study of Twitter use. TechTrends 57(2), 39–45 (2013)Google Scholar
  24. 24.
    Siemens, G.: La enseñanza superior y las promesas y los peligros de las redes sociales. RUSC 8(1), 157–163 (2011)Google Scholar
  25. 25.
    Pérez Dasilva, J., Genaut Arratibel, A., Meso Aierdi, K., Mendiguren Galdospín, T., Marauri Castillo, I., Iturregui Mardaras, L., Rodríguez González, M., Rivero Santamarina, D.: Las empresas en Facebook y Twitter. Situación actual y estrategias comunicativas. Revista Latina de Comunicación Social 68, 676–695 (2013)Google Scholar
  26. 26.
    IAB: Estudio Anual de Redes Sociales, Madrid (2017)Google Scholar
  27. 27.
    Delgado von Eitzen, C.: Blog de ChristianDvE (Beta). 15 Octubre 2016. [Online]. http://www.christiandve.com/2016/10/perfil-usuario-twitter-espana-resultados/. Accessed 9 Oct 2018
  28. 28.
    Observatorio Español del Mercado del Vino: OEMV (2017). [Online]. http://www.oemv.es. Accessed 5 Oct 2018
  29. 29.
    Sogari, G., Pucci, T., Aquilani, B., Zanni, L.: Millennial generation and environmental sustainability: the role of social media in the consumer purchasing behavior for wine. Sustainability 9(10), 1911 (2017)Google Scholar
  30. 30.
    Nielsen: Caracterización del consumidor español de vino. Technical Report. Ministerio de Medio Ambiente y Medio Rural y Marino (2009). Available at: https://www.oemv.es/caracterizacion-del-consumidor-espanol-de-vino-genoma
  31. 31.
    Cochran, C.: Wineries Embracing Social Networking, p. 7. San Francisco Chronicle, San Francisco (2010)Google Scholar
  32. 32.
    Dolan, R., Conduit, J., Fahy, J., Goodman, S.: Facebook for wine brands: an analysis of strategies for Facebook posts and user engagement actions. In: 9th Academy of Wine Business, Adelaide (2016)Google Scholar
  33. 33.
    Fuentes Fernández, R., Vriesekoop, R., Urbano, B.: Social media as a means to access millennial wine consumers. Int. J. Wine Bus. Res. 29(3), 269–284 (2017)Google Scholar
  34. 34.
    Castro Galiana, R.: Blog Las bodegas, los vinos y las políticas de comunicación. 27 Mayo 2014. [Online]. http://castrogaliana.com/las-bodegas-los-vinos-y-las-politicas-de-comunicacion/. Accessed 2 Oct 2018
  35. 35.
    Mariani, A., Pomarici, E., Boatto, V.: The international wine trade: recent trends and critical issues. Wine Econ. Policy 1(1), 24–40 (2012)Google Scholar
  36. 36.
    Foster, M., Francescucci, A., West, B.: Why users participate in online social networks. Int. J. e-Bus. Manag. 4(1), 3–19 (2010)Google Scholar
  37. 37.
    Scott, J.: Social Network Analysis: A Handbook. Sage Publications, London (2000)Google Scholar
  38. 38.
    Kobourov, S.: Force-directed drawing algorithms. In: Tamassia, R. (ed.) Handbook of Graph Drawing and Visualization. CRC Press, Boston (2012)Google Scholar
  39. 39.
    Dearholt, D., Schvaneveldt, R.: Properties of pathfinder networks. In: Schvaneveldt, R.W. (ed.), Pathfinder Associative Networks: Studies in Knowledge Organization, Ablex Publishing Corp. Norwood, NJ, USA, pp. 1–30 (1990)Google Scholar
  40. 40.
    Pancho, D., Alonso, J., Cordón, O., Quirin, A., Magdalena, L.: FINGRAMS: visual representations of fuzzy rule-based inference for expert analysis of comprehensibility. IEEE Trans. Fuzzy Syst. 21(6), 1133–1149 (2013)Google Scholar
  41. 41.
    Serrano, E., Quirin, A., Botia, J., Cordón, O.: Debugging complex software systems by means of pathfinder networks. Inf. Sci. 180(5), 561–583 (2010)Google Scholar
  42. 42.
    Trawinski, K., Chica, M., Pancho, D., Damas, S., Cordón, O.: moGrams: a network-based methodology for visualizing the set of non-dominated solutions in multiobjective optimization. IEEE Trans. Cybern. 48(2), 474–485 (2018)Google Scholar
  43. 43.
    Rashid, U., Viviani, M., Pasi, G.: A graph-based approach for visualizing and exploring a multimedia search result space. Inf. Sci. 370–371, 303–322 (2016)Google Scholar
  44. 44.
    Moya-Anegón, F., Vargas-Quesada, B., Chinchilla-Rodríguez, Z., Corera-Álvarez, E., Muñoz-Fernández, F., Herrero-Solana, V.: Visualizing the marrow of science. J. Assoc. Inf. Sci. Technol. 58(14), 2167–2179 (2007)Google Scholar
  45. 45.
    Vargas-Quesada, B., Moya-Anegón, F.: Visualizing the Structure of Science. Springer, Berlin (2007)Google Scholar
  46. 46.
    Jun, S.P., Park, D.H.: Visualization of brand positioning based on consumer web search information: using social network analysis. Internet Res. 27(2), 381–407 (2017)Google Scholar
  47. 47.
    Quirin, A., Cordón, O., Santamaría, J., Vargas-Quesada, B., Moya-Anegón, F.: A new variant of the pathfinder algorithm to generate large visual science maps in cubic time. Inf. Process. Manag. 44(4), 1611–1623 (2008)Google Scholar
  48. 48.
    Kamada, T., Kawai, S.: An algorithm for drawing general undirected graphs. Inf. Process. Lett. 31(1), 7–15 (1989)MathSciNetzbMATHGoogle Scholar
  49. 49.
    Bastian, M., Heymann, S., Jacomy, M.: Gephi: an open source software for exploring and manipulating networks. In: International AAAI Conference on Weblogs and Social Media (2009)Google Scholar
  50. 50.
    Unwin, A., Theus, M., Hofmann, H.: Graphics of Large Datasets: Visualizing a Million. Springer, Berlin (2008)zbMATHGoogle Scholar
  51. 51.
    Chen, C., Morris, S.: Visualizing evolving networks: minimum spanning trees versus pathfinder networks. In: INFOVIS 2003 (2003)Google Scholar
  52. 52.
    Zizi, M., Beaudouin-Lafon, M.: Accessing hyperdocuments through interactive dynamic maps. In: Proceedings of the 1994 ACM European Conference on Hypermedia Technology (1994)Google Scholar
  53. 53.
    Noel, S., Chu, C., Raghavan, V.: Visualization of document co-citation counts. In: IEEE Symposium on Information Visualisation (2002)Google Scholar
  54. 54.
    Schvaneveldt, R., Durso, F., Dearholt, D.: Network structures in proximity data. Psychol. Learn. Motiv. 24, 249–284 (1989)Google Scholar
  55. 55.
    Fruchterman, T., Reingold, E.: Graph drawing by force-directed placement. Softw. Pract. Exp. 21(11), 1129–1164 (1991)Google Scholar
  56. 56.
    Serrano-Guerrero, J., Olivas, J., Romero, F., Herrera-Viedma, E.: Sentiment analysis: a review and comparative analysis of web services. Inf. Sci. 311, 18–38 (2015)Google Scholar
  57. 57.
    Martínez-Martínez, J., Escandell-Montero, P., Soria-Olivas, E., Martín-Guerrero, J., Serrano-López, A.: A new visualization tool for data mining techniques. Prog. Artif. Intell. 5(2), 137–154 (2016)Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Market ResearchUniversidad Internacional de La RiojaLogroñoSpain
  2. 2.Instituto Andaluz Interuniversitario de Ciencia de Datos e Inteligencia Computacional (DaSCI)University of GranadaGranadaSpain

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