The Collective Impression of Saudis’ Perceptions of Entertainment

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10282)

Abstract

The diversity of human perceptions of entertainment coupled with the continuous emergence of new modes of entertainment have raised a challenge in offering the entertainment environment that is properly aligned with the public interest. Entertainment preferences are known to be shaped by a combination of individuals’ social and cultural background, instability in economic situation, and generational differences. In the Saudi context, many cultural considerations have created a multitude of preferences with regards to accepting newly emerged or imported entertainment methods, particularly due to the distinctive nature of the Saudi cultural context and the complexity of perceptual factors that contribute to shaping individuals’ preferences in the Saudi community. In this paper we propose to utilize visual surveys as a mean for collecting and quantifying urban perceptions of entertainment, with the hope of revealing the current challenges and envisioning the potential directions of improvement. We employ visual surveys as a data collection tool to understand how people’s defined expectations, prior experiences and demographic variables relate to their perceptions with regards to preferred entertainment modes. It is our hope that this research work will open the door toward utilizing the availability of crowdsourcing techniques for comparing and contrasting urban perceptions in other different cultures and contexts.

References

  1. 1.
    Salesses, P., Schechtner, K., Hidalgo, C.A.: The collaborative image of the city: mapping the inequality of urban perception. PLoS ONE 8, 1–12 (2013)CrossRefGoogle Scholar
  2. 2.
    Quercia, D., O’Hare, N.K., Cramer, H.: Aesthetic capital: what makes london look beautiful, quiet, and happy? In: Proceedings of the 17th ACM Conference on Computer supported Cooperative Work & Social Computing (2014)Google Scholar
  3. 3.
    Quercia, D., Pesce, J.P., Almeida, V., Crowcroft, J.: Psychological maps 2.0: a web engagement enterprise starting in London. In: Proceedings of the 22nd International Conference on World Wide Web (2013)Google Scholar
  4. 4.
    Traunmueller, M., Marshall, P., Capra, L.: Crowdsourcing safety perceptions of people: opportunities and limitations. In: Liu, T.Y., Scollon, C., Zhu, W. (eds.) Social Informatics. LNCS, vol. 9471, pp. 120–135. Springer, Cham (2015). doi:10.1007/978-3-319-27433-1_9 CrossRefGoogle Scholar
  5. 5.
    Alsaleh, M., Alomar, N., Alarifi, A.: Smartphone users: understanding how security mechanisms are perceived and new persuasive methods. PloS One 12(3), e0173284 (2017)CrossRefGoogle Scholar
  6. 6.
    Al-Ageel, N., Al-Wabil, A., Badr, G., AlOmar, N.: Human factors in the design and evaluation of bioinformatics tools. Procedia Manuf. 3, 2003–2010 (2015)CrossRefGoogle Scholar
  7. 7.
    Santani, D., Gatica-Perez, D.: Loud and trendy: Crowdsourcing impressions of social ambiance in popular indoor urban places. In: Proceedings of the 23rd ACM international conference on Multimedia (2015)Google Scholar
  8. 8.
    Alomar, N., Wanick, V., Wills, G.: The design of a hybrid cultural model for Arabic gamified systems. Comput. Hum. Behav. 64, 472–485 (2016)CrossRefGoogle Scholar
  9. 9.
    Ruiz-Correa, S., Santani, D., Gatica-Perez, D.: The young and the city: Crowdsourcing urban awareness in a developing country. In: Proceedings of the First International Conference on IoT in Urban Space (2014)Google Scholar
  10. 10.
    Traunmueller, M., Marshall, P., Capra, L.: when you’re a stranger: evaluating safety perceptions of (un) familiar Urban places. In: Proceedings of the Second International Conference on IoT in Urban Space (2016)Google Scholar
  11. 11.
    Liu, S., Cui, W., Wu, Y., Liu, M.: A survey on information visualization: recent advances and challenges. Vis. Comput. 30(12), 1373–1393 (2014)CrossRefGoogle Scholar
  12. 12.
    Cook, K.A., Thomas, J.J.: Illuminating the path: the research and development agenda for visual analytics. IEEE Computer Society, Richland (2005)Google Scholar
  13. 13.
    Chen, W., Guo, F., Wang, F.-Y.: A survey of traffic data visualization. IEEE Trans. Intell. Trans. Syst. 16, 2970–2984 (2015)CrossRefGoogle Scholar
  14. 14.
    Zheng, Y., Wu, W., Chen, Y., Qu, H., Ni, L.M.: Visual analytics in Urban computing: an overview. IEEE Trans. Big Data 2, 276–296 (2016)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia

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