Name
Title | ||
|---|---|---|
DrugTracker - A Community-focused Drug Abuse Monitoring and Supporting System using Social Media and Geospatial Data (Demo Paper). |
Abstract | ||
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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.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3347146.3359076 | SIGSPATIAL/GIS |
Keywords | Field | DocType |
drug abuse, deep learning, visualization, social media | Geospatial analysis,Data science,Social media,Computer science,Substance abuse,Artificial intelligence,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-4503-6909-1 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Han Hu | 1 | 0 | 0.34 |
| NhatHai Phan | 2 | 98 | 10.76 |
| X. Ye | 3 | 158 | 34.16 |
| Ruoming Jin | 4 | 1637 | 91.73 |
| Kele Ding | 5 | 0 | 0.34 |
| Dejing Dou | 6 | 892 | 90.86 |
| Huy T. Vo | 7 | 1035 | 61.10 |