TrendTracker: Temporal, network-based exploration of long-term Twitter trends-Reference-Cited by-同舟云学术

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TrendTracker: Temporal, network-based exploration of long-term Twitter trends

Published:2023-11-06 Issue: Volume:5 Page:441-444
ISSN:
Container-title:Proceedings of the International Conference on Advances in Social Networks Analysis and Mining
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Author:

Ziegler John¹^ORCID,Sindlinger Johannes¹^ORCID,Walther Marina¹^ORCID,Gertz Michael¹^ORCID

Affiliation:

1. Institute of Computer Science, Heidelberg University, Heidelberg, Germany

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3625007.3627335

Reference15 articles.

1. S. Bhulai, P. Kampstra, L. Kooiman, G. Koole, M. Deurloo, and B. Kok, "Trend visualization on Twitter: what's hot and what's not?" in 1st International Conference on Data Analytics, 2012, pp. 43--48.

2. Z. Doshi, S. Nadkarni, K. Ajmera, and N. Shah, "Tweeranalyzer: Twitter trend detection and visualization," in 2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA). IEEE, 2017, pp. 1--6.

3. F. Wanner, A. Weiler, and T. Schreck, "Topic Tracker: Shape-based Visualization for Trend and Sentiment Tracking in Twitter," in VisWeek, 2012.

4. D. Stojanovski, I. Dimitrovski, and G. Madjarov, "Tweetviz: Twitter data visualization," Proceedings of the data mining and data warehouses, vol. 1, no. 2, 2014.

5. TTLocVis: A Twitter Topic Location Visualization Package

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