Multi-Model Investigative Exploration of Social Media Data with boutique: A Case Study in Public Health
This work addresses the need for public health researchers to efficiently explore and visualize social media data to evaluate campaign effectiveness, though it appears incremental as it builds on existing investigative exploration methods.
The researchers tackled the problem of analyzing social media data to assess public awareness of HIV prevention campaigns by developing boutique, a multi-step visualization and exploration system that integrates heterogeneous data from a polystore and uses computation during investigation, as demonstrated in a real-life case study.
We present our experience with a data science problem in Public Health, where researchers use social media (Twitter) to determine whether the public shows awareness of HIV prevention measures offered by Public Health campaigns. To help the researcher, we develop an investigative exploration system called boutique that allows a user to perform a multi-step visualization and exploration of data through a dashboard interface. Unique features of boutique includes its ability to handle heterogeneous types of data provided by a polystore, and its ability to use computation as part of the investigative exploration process. In this paper, we present the design of the boutique middleware and walk through an investigation process for a real-life problem.