Name
Title | ||
|---|---|---|
Leveraging machine learning-based approaches to assess human papillomavirus vaccination sentiment trends with Twitter data. |
Abstract | ||
|---|---|---|
Our efforts on sentiment analysis for newly approved HPV vaccines provide us an automatic and instant way to extract public opinion and understand the concerns on Twitter. Our approaches can provide a feedback to public health professionals to monitor online public response, examine the effectiveness of their HPV vaccination promotion strategies and adjust their promotion plans. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1186/s12911-017-0469-6 | BMC Med. Inf. & Decision Making |
Keywords | Field | DocType |
Hierarchical classification,Human papillomavirus vaccines,Machine learning,Sentiment analysis,Twitter | Public health,Data mining,Social media,Sentiment analysis,Vaccination,Public opinion,Papillomavirus Vaccines,Medicine,HPV vaccines,Vaccination Refusal | Journal |
Volume | Issue | ISSN |
17 | 2 | 1472-6947 |
Citations | PageRank | References |
6 | 0.47 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jingcheng Du | 1 | 30 | 16.40 |
| jun xu | 2 | 58 | 9.42 |
| Hsing-yi Song | 3 | 10 | 1.70 |
| Cui Tao | 4 | 35 | 12.77 |