| Title |
Deep learning for detecting inappropriate content in text
|
|---|---|
| Published in |
International Journal of Data Science and Analytics, December 2017
|
| DOI | 10.1007/s41060-017-0088-4 |
| Authors |
Harish Yenala, Ashish Jhanwar, Manoj K. Chinnakotla, Jay Goyal |
X Demographics
The data shown below were collected from the profiles of 25 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 | 6 | 24% |
| Canada | 3 | 12% |
| United Kingdom | 3 | 12% |
| India | 2 | 8% |
| Israel | 1 | 4% |
| France | 1 | 4% |
| Unknown | 9 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 24 | 96% |
| Practitioners (doctors, other healthcare professionals) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 133 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 19 | 14% |
| Student > Bachelor | 13 | 10% |
| Student > Ph. D. Student | 11 | 8% |
| Researcher | 7 | 5% |
| Student > Doctoral Student | 6 | 5% |
| Other | 14 | 11% |
| Unknown | 63 | 47% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 52 | 39% |
| Engineering | 4 | 3% |
| Unspecified | 3 | 2% |
| Biochemistry, Genetics and Molecular Biology | 2 | 2% |
| Social Sciences | 2 | 2% |
| Other | 6 | 5% |
| Unknown | 64 | 48% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 30 January 2024.
All research outputs
#2,046,158
of 25,323,244 outputs
Outputs from International Journal of Data Science and Analytics
#8
of 245 outputs
Outputs of similar age
#45,374
of 455,762 outputs
Outputs of similar age from International Journal of Data Science and Analytics
#1
of 7 outputs
Altmetric has tracked 25,323,244 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 245 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has done particularly well, scoring higher than 97% 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 455,762 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them