Health-related hypothesis generation using social media data
Bibliographic Data
| ID | 16859203 |
|---|---|
| Authors | Jon Parker (Johns Hopkins University, corresponding author), Andrew Yates (0000-0002-5970-880X, Georgetown University), Nazli Goharian (Georgetown University), Ophir Frieder (0000-0001-5076-8171, Georgetown University) |
| Year | 2015 |
| Volume | 5 |
| Issue | 1 |
| Publication date | 2015-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-014-0239-8 |
| OpenAlex | W2014338459 |
| Language | EN |
| Citations received | 2 |
| References cited | 30 |
Computer security · Data science · Health care · Internet privacy · Political science · Public health · Raw data · Social media · World Wide Web · Computer Science · Data-Driven Disease Surveillance · Influenza Virus Research Studies · Medicine · Misinformation and Its Impacts
Time series analysis
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Detecting influenza epidemics using search engine query data
Earthquake shakes Twitter users
Predicting Elections with Twitter
Social Media Use in the United States
Twitter power
Would school closure for the 2009 H1N1 influenza epidemic have been worth the cost
The Global Public Health Intelligence Network and Early Warning Outbreak Detection
From Tweets to Polls
| Citations per year | 0.4 |
|---|---|
| Citation span | 2021 - 2026 (6) |
| Highly cited | No |