Drugtracker: A community-focused drug abuse monitoring and supporting system using social media and geospatial data (Demo Paper)

Document Type

Conference Proceeding

Publication Date

11-5-2019

Abstract

In this paper, we present a community-focused drug abuse monitoring and supporting system, called DrugTracker, that utilizes social media and geospatial data in near real-time. Through the system, users can: (1) Detect drug abuse risk behaviors from social media platforms, e.g., Twitter; (2) Analyze drug abuse risk behaviors by querying consolidated and live datasets with keywords, spatial entities, and time constraints; and (3) Explore the query results and associated data through a web-based user interface in thematic choropleth, heatmap, and statistical charts. To protect the privacy of the Twitter users, whose data is collected, the system automatically hides the re-identification elements in tweets and aggregates the geo-tags into areas such as census tracts. For the demonstration purpose, our DrugTracker system is populated with a database that contains about 10 million tweets from the year 2017, that were annotated as drug abuse risk behavior positive by our deep learning model.

Identifier

85076966800 (Scopus)

ISBN

[9781450369091]

Publication Title

GIS Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

External Full Text Location

https://doi.org/10.1145/3347146.3359076

First Page

564

Last Page

567

Grant

1850094

Fund Ref

National Science Foundation

This document is currently not available here.

Share

COinS