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

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


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.


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



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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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