Social Relationship Ranking on the Smart Internet
The changes in population demography and technology have made social connections more and more difficult, although fundamental to human nature, health, and well-being. A review of the theory and measurement evolution of social relations and their early empirical evidence is analyzed in this chapter. We consider how social relationships have changed over time and how the fundamental characteristics of social relations have shifted through analysis of different techniques for the digital ranking. The emerging impact of technology on contacts, particularly on the evolving ways in which technology can be used to strengthen, decrease, maintain, or prevent social relations is also discussed. The role and influence of the smart Internet in the negative as well as in the positive aspects of these new technologies on the well-being of smart people are elaborated. Successful navigation of our complex social environment calls for the ability to identify and judge others’ relativity. Social comparison processes are therefore very important and contribute to intelligent individuals and urban development for efficient interpersonal decision-making.
KeywordsSmart city Smart people Collaborative ranking Social relationships Urban computing Machine learning Smart Internet
- 2.Rabadiya, K., Makwana, A., Jardosh, S.: Revolution in networks of smart objects: social internet of things. In: 2017 International Conference on Soft Computing and Its Engineering Applications (icSoftComp). IEEE, Piscataway (2017). https://doi.org/10.1109/icsoftcomp.2017.8280086CrossRefGoogle Scholar
- 3.Rafailidis, D., Crestani, F.: Collaborative ranking with social relationships for top-N recommendations. In: Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR ‘16. IEEE, Piscataway (2016). https://doi.org/10.1145/2911451.2914711CrossRefGoogle Scholar
- 8.Park, G., Lee, S., Lee, S.: To enhance web search based on topic Sensitive_social Relationship ranking algorithm in Social networks. In: IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology. IEEE, Piscataway (2009). https://doi.org/10.1109/wi-iat.2009.322CrossRefGoogle Scholar
- 9.Ma, C., Wang, Y., Liu, H., Gui, H., Zhu, W., Shi, X., Li, X.: An approach to social relationship ranking on internet-based social platforms by tempo-spatial data mining using location prediction technique. In: IEEE International Congress on Big Data. IEEE, Piscataway (2015). https://doi.org/10.1109/bigdatacongress.2015.56CrossRefGoogle Scholar
- 12.Psomakelis, E., Aisopos, F., Litke, A., Tserpes, K., Kardara, M., Campo, P.M.: Big IoT and social networking data for smart cities - algorithmic improvements on big data analysis in the context of RADICAL City applications. In: Proceedings of the 6th International Conference on Cloud Computing and Services Science. Cornell University, Ithaca (2016). https://doi.org/10.5220/0005934503960405CrossRefGoogle Scholar