Digital Society: A Computing Science Prospective

  • Hrushikesha MohantyEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11319)


Unprecedented connectivity over Internet has given rise to digital society where individuals turn to netizens in cyberspace. The support that computing science can offer enabling netizens to active citizens is of interest for computing professionals. From computing science perspective, this paper addresses some of the issues like modelling a netizen, communication, pressure group creation, electronic voting, law making and education for digital society; scopes the research challenges the issues offer.


Digital society Netizen modelling Social communication Pressure group management Electronic voting and law making 


  1. 1.
    Bifet, A., Frank, E.: Sentiment knowledge discovery in twitter streaming data. In: Pfahringer, B., Holmes, G., Hoffmann, A. (eds.) DS 2010. LNCS (LNAI), vol. 6332, pp. 1–15. Springer, Heidelberg (2010). Scholar
  2. 2.
    Chaum, D., Essex, A., Carback, R.: Scantagrity: End-to-End voter-verifiable optical-scan voting. IEEE Secur. Priv. (2008)Google Scholar
  3. 3.
    He, C., Li, H., Fei, X., Yang, A., Tang, Y., Zhu, J.: A topic community based method for friend recommendation in large scale online social networks. Concurr. Comput.: Pract. Exp. 29, 1–20 (2017)Google Scholar
  4. 4.
    Borch, C., Lind, U.: The mobile parliament: taking regional matters of concern seriously; Scandinavian. J. Soc. Theory 10(1), 69–86 (2009)Google Scholar
  5. 5.
    Platglaou, G.: Sentiment-based even detection in Twitter. J. Assoc. Inf. Sci. Technol. 67(7), 1576–1587 (2016)CrossRefGoogle Scholar
  6. 6.
    Persson, G.: Love, affiliation, and emotional recognition in \(kmpamalm\): the social role of emotional language in twitter discourse. Soc. Media\(+\) Soc. January-March 2017, 1–11 (2017)Google Scholar
  7. 7.
    Lamport, L.: The part-time parliament. ACM Trans. Comput. Syst. 16(2), 133–169 (1998)CrossRefGoogle Scholar
  8. 8.
    Bing, L., Chan, K.C.C., Ou, C.: Public sentiment analysis in tweeter data for prediction of a company’s stock price movements. In: IEEE 11th International Conference e-Business Engineering, pp. 232–239 (2014)Google Scholar
  9. 9.
    Mohanty, H.: Person habitat and migration modeling. In: IEEE INDICON (2011)Google Scholar
  10. 10.
    Mohanty, H.: Computational social science: a bird’s eye view. In: Hota, C., Srimani, P.K. (eds.) ICDCIT 2013. LNCS, vol. 7753, pp. 319–333. Springer, Heidelberg (2013). Scholar
  11. 11.
    Mohanty, H., Prasad, K., Shyamasundar, R.K.: Trust assessment in web services: an extension to jUDDI. In: ICEBE, pp. 759–762 (2007)Google Scholar
  12. 12.
    Imran, M., Castillo, C., Diaz, F., Vieweg, S.: Processing social media messages in mass emergency: a survey. ACM Comput. Surv. 47(4), 1–38 (2015)CrossRefGoogle Scholar
  13. 13.
    Simpson, R., Storer, T.: Third-party verifiable voting system: addressing motivation and incentives in e-voting. J. Inf. Secur. Appl. 38, 132–138 (2018)Google Scholar
  14. 14.
    Wayne Gladstone’ The Internet apocalypse Trilogy, NovelGoogle Scholar
  15. 15.
    Fang, Y., Zhang, H., Ye, Y., Li, X.: Detecting hot topics from Twitter: a multiview approach. J. Inf. Sci. 40(5), 578–593 (2014)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.KIIT Deemed UniversityBhubaneswarIndia
  2. 2.University of HyderabadHyderabadIndia

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