This paper intends to develop an interactive, comprehensive information visualization platform of Instagram hashtag analysis. Instagram hashtags has developed themselves into all different kinds of group or communities for users to share hobbies and find similar friends. In order to analyze topic influence and user interest trend from Instagram, which contains billions of end-users and has worldwide influence, hashtag analysis is necessary to gather such information and compare the proportion of people involving in each tags and rank them to visualize. The visualization is developed in 3D space and consists of time-varying data flow of tags, together with tag comparison analysis, as well as event researches. In the rest of the paper, we mainly discuss the design idea and the development process of the system. An example of the system design work will be shown in the discussion, which involves 4 popular hashtags discussed on Instagram and are shown on the system, displayed as an 3D histogram, together with another comparison histogram to compare different tags, as well as an event view in the back.
Chen, S., Chen, S., Wang, Z., Liang, J., Yuan, X., Cao, N., & Wu, Y. (2016, October). D-map: Visual analysis of ego-centric information diffusion patterns in social media. In 2016 IEEE Conference on Visual Analytics Science and Technology (VAST) (pp. 41-50). IEEE.
de_Campos Filho, A. S., Freitas, F., Gomes, A. S., & Vitorino, J. (2012, July). Brandmap: An information visualization platform for brand association in blogosphere. In 2012 16th International Conference on Information Visualisation (pp. 316-320). IEEE.
Finch, J. L., & Flenner, A. R. (2016). Using Data Visualization to Examine an Academic Library Collection. College & Research Libraries, 77(6), 765-778.
Hong, S., Wang, F., & Zeng, Z. (2016, October). Design and implementation of data visualization in media manuscripts transmission system. In 2016 First IEEE International Conference on Computer Communication and the Internet (ICCCI) (pp. 32-36). IEEE.
Itoh, M., Toyoda, M., & Kitsuregawa, M. (2013, July). Visualizing time-varying topics via images and texts for inter-media analysis. In 2013 17th International Conference on Information Visualisation (pp. 568-576). IEEE.
Windhager, F., Federico, P., Schreder, G., Glinka, K., Dörk, M., Miksch, S., & Mayr, E. (2018). Visualization of cultural heritage collection data: State of the art and future challenges. IEEE transactions on visualization and computer graphics, 25(6), 2311-2330.