Web-Based Visual Analytics for Social Media

Authors

  • Daniel Best Pacific Northwest National Laboratory
  • Joseph Bruce Pacific Northwest National Laboratory
  • Scott Dowson Pacific Northwest National Laboratory
  • Oriana Love Pacific Northwest National Laboratory
  • Liam McGrath Pacific Northwest National Laboratory

DOI:

https://doi.org/10.1609/icwsm.v6i4.14363

Abstract

Social media provides a rich source of data that reflects current trends on a multitude of topics. The data can be harvested from Twitter, Facebook, blogs, and other social applications. The high rate of adoption of social media has created a domain that is difficult to analyze, due to the ever-expanding volume of data. Information visualization is key in drawing out features of interest in social media. The Scalable Reasoning System is an application that couples a back-end server equipped with analysis algorithms and an intuitive visual in- terface to allow for investigation. We provide a componentized system that can be rapidly adapted to user needs. The in- formation in which they are most interested is featured prominently in the application. As an example, we have developed a weather and traffic monitoring application for use by emergency operators in the city of Seattle.

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Published

2021-08-03

How to Cite

Best, D., Bruce, J., Dowson, S., Love, O., & McGrath, L. (2021). Web-Based Visual Analytics for Social Media. Proceedings of the International AAAI Conference on Web and Social Media, 6(4), 2-5. https://doi.org/10.1609/icwsm.v6i4.14363