| Title |
Big data would not lie: prediction of the 2016 Taiwan election via online heterogeneous information
|
|---|---|
| Published in |
EPJ Data Science, September 2018
|
| DOI | 10.1140/epjds/s13688-018-0163-7 |
| Authors |
Zheng Xie, Guannan Liu, Junjie Wu, Yong Tan |
X Demographics
The data shown below were collected from the profiles of 20 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 Kingdom | 2 | 10% |
| United States | 2 | 10% |
| Indonesia | 1 | 5% |
| Spain | 1 | 5% |
| Unknown | 14 | 70% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 60% |
| Scientists | 7 | 35% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 64 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 13 | 20% |
| Student > Doctoral Student | 7 | 11% |
| Student > Ph. D. Student | 6 | 9% |
| Student > Master | 6 | 9% |
| Professor > Associate Professor | 4 | 6% |
| Other | 11 | 17% |
| Unknown | 17 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 16 | 25% |
| Computer Science | 11 | 17% |
| Engineering | 6 | 9% |
| Business, Management and Accounting | 4 | 6% |
| Unspecified | 2 | 3% |
| Other | 6 | 9% |
| Unknown | 19 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 20. 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 2021.
All research outputs
#1,822,108
of 25,064,526 outputs
Outputs from EPJ Data Science
#155
of 427 outputs
Outputs of similar age
#37,467
of 343,275 outputs
Outputs of similar age from EPJ Data Science
#13
of 20 outputs
Altmetric has tracked 25,064,526 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 427 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.7. This one has gotten more attention than average, scoring higher than 63% 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 343,275 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 89% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.