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Analyzing on User Behavior and User Experience of Social Network Services

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Simulation Tools and Techniques (SIMUtools 2019)

Abstract

The user behavior characteristics of mobile social network services are beneficial for evaluating the user experience, and the test cases and test scenarios should be designed according to the user behavior characteristics. The current researches have been heavily addressed on the action sequence and the frequency distribution of user behavior. There is little research on the user’s action triggering network flow under different scenarios. This paper analyzes the distribution character of user actions, and tests the waiting time of different user actions in different scenes. The results suggest that the complex scenarios can be consisted of some typical user behaviors.

This work is partly supported by the Natural Science Foundation of Jiangsu Province of China (No. BK20161165), the applied fundamental research Foundation of Xuzhou of China (No. KC17072), and the Open Fund of the Jiangsu Province Key Laboratory of Intelligent Industry Control Technology, Xuzhou University of Technology.

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References

  1. Wang, Y., Li, P.L., Jiao, L., et al.: A data-driven architecture for personalized QoE management in 5G wireless networks. IEEE Wirel. Commun. 24(1), 102–110 (2017)

    Article  Google Scholar 

  2. Jiang, D., Wang, W., Shi, L., Song, H.: A compressive sensing-based approach to end-to- end network traffic reconstruction. IEEE Trans. Netw. Sci. Eng. (2018). https://doi.org/10.1109/tnse.2018.2877597

  3. Jiang, D., Huo, L., Song, H.: Rethinking behaviors and activities of base stations in mobile cellular networks based on big data analysis. IEEE Trans. Netw. Sci. Eng. 1(1), 1–12 (2018)

    Article  Google Scholar 

  4. Jiang, D., Huo, L., Li, Y.: Fine-granularity inference and estimations to network traffic for SDN. PLoS ONE 13(5), 1–23 (2018)

    Google Scholar 

  5. Chen, L., Jiang, D., Song, H., et al.: A lightweight end-side user experience data collection system for quality evaluation of multimedia communications. IEEE Access 2018(6), 15408–15419 (2018)

    Article  Google Scholar 

  6. Jin, Y., Duffield, N., Haffner, P., et al.: Can’t see forest through the trees. In: The Proceedings of 9th Workshop on Mining and Learning with Graphs, San Diego, USA (2011)

    Google Scholar 

  7. Schneider, F., Feldmann, A., Krishnamurthy, B., et al.: Understanding online social network usage from a network perspective. In: Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement Conference, Chicago, USA (2009)

    Google Scholar 

  8. Zhang, S., Zhao, Z., Guan, H., et al.: A modified poisson distribution for smartphone background traffic in cellular networks. Int. J. Commun. Syst. 30(6) (2017). https://doi.org/10.1002/dac.3117

    Article  Google Scholar 

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Correspondence to Lei Chen .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Bao, R., Chen, L., Cui, P. (2019). Analyzing on User Behavior and User Experience of Social Network Services. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-32216-8_17

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  • DOI: https://doi.org/10.1007/978-3-030-32216-8_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-32215-1

  • Online ISBN: 978-3-030-32216-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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