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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Filtering big data from social media – Building an early warning system for adverse drug reactions
|
|---|---|
| Published in |
Journal of Biomedical Informatics, February 2015
|
| DOI | 10.1016/j.jbi.2015.01.011 |
| Pubmed ID | |
| Authors |
Ming Yang, Melody Kiang, Wei Shang |
| Abstract |
Adverse Drug Reactions (ADRs) are believed to be a leading cause of death in the world. Pharmacovigilance systems are aimed at early detection of ADRs. With the popularity of social media, Web forums and discussion boards become important sources of data for consumers to share their drug use experience, as a result may provide useful information on drugs and their adverse reactions. In this study, we propose an automated ADR related posts filtering mechanism using text classification methods. In real-life settings, ADR related messages are highly distributed in social media, while non-ADR related messages are unspecific and topically diverse. It is expensive to manually label a large amount of ADR related messages (positive examples) and non-ADR related messages (negative examples) to train classification systems. To mitigate this challenge, we examine the use of a partially supervised learning classification method to automate the process. |
X Demographics
The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 44% |
| France | 2 | 13% |
| Italy | 2 | 13% |
| India | 1 | 6% |
| Unknown | 4 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 88% |
| Scientists | 1 | 6% |
| Practitioners (doctors, other healthcare professionals) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 338 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | <1% |
| Switzerland | 1 | <1% |
| Brazil | 1 | <1% |
| Ecuador | 1 | <1% |
| Spain | 1 | <1% |
| United Kingdom | 1 | <1% |
| Unknown | 331 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 66 | 20% |
| Student > Master | 63 | 19% |
| Researcher | 34 | 10% |
| Student > Bachelor | 28 | 8% |
| Student > Doctoral Student | 21 | 6% |
| Other | 70 | 21% |
| Unknown | 56 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 81 | 24% |
| Medicine and Dentistry | 45 | 13% |
| Business, Management and Accounting | 24 | 7% |
| Engineering | 23 | 7% |
| Social Sciences | 14 | 4% |
| Other | 74 | 22% |
| Unknown | 77 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 January 2016.
All research outputs
#3,333,477
of 25,394,764 outputs
Outputs from Journal of Biomedical Informatics
#194
of 2,247 outputs
Outputs of similar age
#47,157
of 369,651 outputs
Outputs of similar age from Journal of Biomedical Informatics
#4
of 32 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,247 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 369,651 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.