Skip to main content

Intelligent Observatory System on Information Technologies, Social Networks and Infrared to Analyze and Predict Social Mutations

  • Conference paper
  • First Online:
Advanced Intelligent Systems for Sustainable Development (AI2SD’2019) (AI2SD 2019)

Abstract

The use of new technologies and industrialization in everyday life have a direct impact on the consequences of cultural, scientific, and demographic change that diversifies and densifies social relations, and makes individuals more interdependent and complementary. The large amount of data (Big Data) derived from the use of New Technologies solutions to generate a knowledge emphasizes the emergence of new values born of Protestantism and which encourage individuals to search for perfection in economic and social activities. The main objective of this paper is to set up an Intelligent Observatory System on Information Technologies and Social Networks to Analyze, Predict, Explain and Better Understand Social Mutations. Therefore, the system that we propose in this paper puts forward social indicators through learning systems and data mining solutions, for qualitative measures and optimized intelligent calculus based on the behavior and interaction of individuals and/or and social groups. Allowing to take all the necessary measures to foresee the risks and to quantify the rate of the negative impact on the social mutation, and to understand the stakes of the social relations in a given society (For example: the passage from an ideology to a other, disappearance of cultures and appearance of others). This article discusses challenges and role of Big Data Analytics in Social Mutations sector through the use of the new technologies. Following a qualitative approach, this paper reveals the actions currently undertaken by the two categories in the Morocain societies in order to understand their internal and external behaviour.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Agrawal, R., Rajagopalan, S., Srikant, R., Xu, Y.: Mining newsgroups using networks arising from social behavior. In: Proceedings of the 12th International Conference on World Wide Web (2003)

    Google Scholar 

  2. Anand, P., Walker, M., Abbott, R., Fox Tree, J.E., Bowmani, R., Minor, M.: Cats rule and dogs drool! Classifying stance in online debate. In: Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (2011)

    Google Scholar 

  3. Bach, S., Huang, B., London, B., Getoor, L.: Hinge-loss Markov random fields: convex inference for structured prediction. In: Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence (2013)

    Google Scholar 

  4. Barahona, F.: On the computational complexity of Ising spin glass models. J. Phys. A: Math. Gen. 15(10), 3241–3253 (1982)

    Article  MathSciNet  Google Scholar 

  5. Blitzer, J., Dredze, M., Pereira, F.: Biographies, bollywood, boom-boxes and blenders: domain adaptation for sentiment classification. In: Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics (2007)

    Google Scholar 

  6. Boyd, S., Parikh, N., Chu, E., Peleato, B., Eckstein, J.: Distributed optimization and statistical learning via the alternating direction method of multipliers. Found. Trends Mach. Learn. 3(1), 1–122 (2011)

    Article  Google Scholar 

  7. Broecheler, M., Mihalkova, L., Getoor, L.: Probabilistic similarity logic. In: Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (2010)

    Google Scholar 

  8. Cartwright, D., Harary, F.: Structure balance: a generalization of Heider’s theory. Psychol. Rev. 63(5), 277–293 (1956)

    Article  Google Scholar 

  9. Dunbar, R.I.: Gossip in evolutionary perspective. Rev. Gen. Psychol. 8(2), 100–110 (2004)

    Article  Google Scholar 

  10. Barrett, L.F., Russell, J.A.: Independence and bipolarity in the structure of affect. J. Pers. Soc. Psychol. 74(4), 967–984 (1998)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Israel Ezznati .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ezznati, I., Cherrat, L., Ezziyyani, M. (2020). Intelligent Observatory System on Information Technologies, Social Networks and Infrared to Analyze and Predict Social Mutations. In: Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2019). AI2SD 2019. Advances in Intelligent Systems and Computing, vol 1104. Springer, Cham. https://doi.org/10.1007/978-3-030-36671-1_35

Download citation

Publish with us

Policies and ethics