Skip to main content

Toward Building of Visualization Method to Highlight Top Users’ Trends in Social Networks

  • Conference paper
  • First Online:
Resilient and Responsible Smart Cities

Abstract

Social media plays an essential role in people’s daily life. It is prevalent among the young generation. Social media applications, such as Microblog Sina Weibo, Twitter, Facebook, Instagram, are occupying significant positions in social connection and human being communication. Social media applications, like Weibo, provide the function of publishing, viewing, commenting, and sharing information. They also provide a platform for people to freely express their true feelings and opinions about the events through comment, retweets, and thumbs up. Information transmission on Weibo is real time, timely, and continuous, which helps track public interest and attitudes on a particular topic. Based on the information transmission on these similar social media networks, the sense of time, space, and strangeness between publishers and audiences is eliminated. Using information visualization can make the public opinions in social networks clearly show. The layered display composed of flower graph, radar graph, and pie chart allows users to have an in-depth understanding of popular trends from comprehensive to detailed. We choose Sina Weibo and 5G themes as visualization examples to demonstrate visualization methods applicable to all social media networks. We used a questionnaire survey to evaluate our visualization model. The analysis result shows that the model is creative, accurate, and easy to understand. In the end, the Social Network Public Emotion Information Visualization Model (SNPEIVM) is put forward.

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 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover 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

  • Calderon, F., Chang, C. H., Argueta, C., Saravia, E., & Chen, Y. S. (2015). Analyzing event opinion transition through summarized emotion visualization. In Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 (pp. 749–752).

    Google Scholar 

  • Funayama, T., Yamamoto, Y., & Uchida, O. (2017). Development of visualization application of tweet data for extracting information in case of disaster. In 2017 15th International Conference on ICT and Knowledge Engineering (ICT&KE) (pp. 1–5). IEEE.

    Google Scholar 

  • Lu, J., Yu, X., & Wan, W. (2014). Visualization research of the tweet diffusion in the microblog network. In 2014 International Conference on Audio, Language and Image Processing (pp. 592–595). IEEE.

    Google Scholar 

Download references

Acknowledgements

This work has supported by the Xiamen University Malaysia Research Fund (XMUMRF) (Grant No: XMUMRF/2019-C3/IECE/0007).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Raja Majid Mehmood .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Quanwen, L., Yan, Z., Mehmood, R.M. (2021). Toward Building of Visualization Method to Highlight Top Users’ Trends in Social Networks. In: Ujang, N., Fukuda, T., Pisello, A.L., Vukadinović, D. (eds) Resilient and Responsible Smart Cities. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-030-63567-1_10

Download citation

Publish with us

Policies and ethics