The Diffusion of News Applying Sentiment Analysis and Impact on Human Behavior Through Social Media

  • Myriam PeñafielEmail author
  • Rosa Navarrete
  • Maritzol Tenemaza
  • Maria Vásquez
  • Diego Vásquez
  • Sergio Luján-Mora
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 965)


The Web is the largest source of information today, a group of these data is the news that is disseminated using Social Networks which are information that needs to be processed in order to know what is its main use in a way that contributes to understanding the impact of these media in the dissemination of news. To solve this problem, we propose the use of data mining techniques such as the Sentiment Analysis to validate the information that comes from social media. The objective of this research is to make a proposal of a method of Systematic Mapping that allows determining the state of the art related to the investigations of the diffusion of news applying Sentiment Analysis and impact on human behavior through Social Media. This initial research presented as a case study a time range until 2017 in research related to the news that uses Data mining techniques like to sentiment analysis for social media in major search engines.


Data mining Text analysis Sentiment analysis News Social media Human behavior Systematic mapping 


  1. 1.
    Gandomi, A., Murtaza, H.: Beyond the hype: big data concepts, methods, and analytics. Int. J. Inf. Manage. 35(2), 137–144 (2015)CrossRefGoogle Scholar
  2. 2.
    Warren-Payne, A.: 13 epic stats and facts from The State of Social webinar.
  3. 3.
    Kaplan, A.M., Haenlein, M.: Users of the world, unite! The challenges and opportunities of social media. Bus. Horiz. 53(1), 59–68 (2010)CrossRefGoogle Scholar
  4. 4.
    Cavazza, F.: Social media landscape 2017.
  5. 5.
    Vinodhini, G., Chandrasekaran, R.-M.: Sentiment analysis and opinion mining: a survey. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 2(6), 282–292 (2012)Google Scholar
  6. 6.
    Peñafiel, M., Vásquez, S., Vásquez, D., Zaldumbide, J., Luján-Mora, S.: Data mining and opinion mining: a tool in educational context. In: Proceedings of the International Conference on Mathematics and Statistics (ICoMS2018), pp. 74–78. ACM (2018)Google Scholar
  7. 7.
    Liu, B.: Sentiment analysis and opinion mining. Synth. Lect. Hum. Lang. Technol. 5(1), 1–167 (2012)CrossRefGoogle Scholar
  8. 8.
    Del-Vicario, M., Zolloa, F., Caldarellia, G., Scalab, A., Quattrociocchia, W.: Mapping social dynamics on Facebook: The Brexit debate. Soc. Netw. 50, 6–16 (2017)CrossRefGoogle Scholar
  9. 9.
    Kitchenham, B.: Procedures for performing systematic reviews. Keele, UK, Keele Univ. 33, 1–26 (2004)Google Scholar
  10. 10.
    Araujo-Alonso, M.: Las revisiones sistemáticas. Medwave.
  11. 11.
    Petersen, K., Vakkalanka, S., Kuzniarz, L.: Guidelines for conducting systematic mapping studies in software engineering: an update. Inf. Softw. Technol. 64, 1–18 (2015)CrossRefGoogle Scholar
  12. 12.
    Kitchenham, B., Budgen, D., Brereton, O.: Using mapping studies as the basis for further research–a participant-observer case study. Inf. Soft. Technol. 53(6), 63–651 (2010)Google Scholar
  13. 13.
    Smeeton, N.-C.: Early history of the kappa statistic. Biometrics 41, 795 (1985)Google Scholar
  14. 14.
    Marshall, C., Brereton, P., Kitchenham, B.: Tools to support systematic reviews in software engineering: a feature analysis. In: Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering, pp. 1–13. ACM (2014)Google Scholar
  15. 15.
    Souza, E., Vitório, D., Castro, D., Oliveira, A., Gusmão, C.: Characterizing opinion mining: a systematic mapping study of the Portuguese language. In: International Conference on Computational Processing of the Portuguese Language, pp. 122–127 (2016)Google Scholar
  16. 16.
    Adedoyin-Olowe, M., Medhat-Gaber, M., Frederic S.: A survey of data mining techniques for social media analysis. arXiv preprint arXiv: 1312.4617 (2013)Google Scholar
  17. 17.
    Ravi, K., Ravi, V.: A survey on opinion mining and sentiment analysis: tasks, approaches and applications. Knowl. Based Syst. 89, 1–46 (2015)CrossRefGoogle Scholar
  18. 18.
    Martín-Valdivia, M.-T., Martínez-Cámara, E., Perea-Ortega, J.-M., Ureña-López, L.-A.: Sentiment polarity detection in Spanish reviews combining supervised and unsupervised approaches. Expert Syst. Appl. 40(10), 3934–3942 (2013)CrossRefGoogle Scholar
  19. 19.
    Peñafiel, M., Navarrete, R., Lujan-Mora, S., Zaldumbide, J.: Bridging the gaps between technology and engineering education. Int. J. Eng. Educ. 34(5), 1479–1494 (2018)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Myriam Peñafiel
    • 1
    Email author
  • Rosa Navarrete
    • 1
  • Maritzol Tenemaza
    • 1
  • Maria Vásquez
    • 1
  • Diego Vásquez
    • 2
  • Sergio Luján-Mora
    • 3
  1. 1.Escuela Politécnica NacionalQuitoEcuador
  2. 2.ESPE-UGTLatacungaEcuador
  3. 3.University of AlicanteAlicanteSpain

Personalised recommendations