- By:
- Choi, Minsuk; Shin, Sungbok; Choi, Jinho; Langevin, Scott; Bethune, Christopher; Horne, Philippe; Kronenfeld, Nathan; Kannan, Ramakrishnan ; Drake, Barry; Park, Haesun; CHOO, JAEGUL
- Page Number:
- 583
- Book Title:
- CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
- Publication Date:
- March 12, 2026
- Conference Name:
- Conference on Human Factors in Computing Systems (CHI 2018)
- Conference Location:
- Montreal, Canada
- Conference Sponsor:
- Alibaba Group, Bloomberg, IBM Research, Facebook, Google, Microsoft, Oath,
- View DOI Listing:
- https://doi.org/10.1145/3173574.3174157
Abstract
Detecting anomalous events of a particular area in a timely manner is an important task. Geo-tagged social media data are useful resource for this task; however, the abundance of everyday language in them makes this task still challenging. To address such challenges, we present TopicOnTiles, a visual analytics system that can reveal information relevant to anomalous events in a multi-level tile-based map interface by using social media data. To this end, we adopt and improve a recently proposed topic modeling method that can extract spatio-temporally exclusive topics corresponding to a particular region and a time point. Furthermore, we utilize a tile-based map interface to efficiently handle large-scale data in parallel. Our user interface effectively highlights anomalous tiles using our novel glyph visualization that encodes the degree of anomaly computed by our exclusive topic modeling processes. To show the effectiveness of our system, we present several usage scenarios using real-world datasets as well as comprehensive user study results.
