| Title |
Deep learning in finance and banking: A literature review and classification
|
|---|---|
| Published in |
Frontiers in Business Research in China, June 2020
|
| DOI | 10.1186/s11782-020-00082-6 |
| Authors |
Jian Huang, Junyi Chai, Stella Cho |
X Demographics
The data shown below were collected from the profiles of 112 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 | 14 | 13% |
| India | 5 | 4% |
| France | 5 | 4% |
| Germany | 4 | 4% |
| United Kingdom | 4 | 4% |
| Belgium | 3 | 3% |
| Nigeria | 3 | 3% |
| Canada | 3 | 3% |
| Sri Lanka | 2 | 2% |
| Other | 24 | 21% |
| Unknown | 45 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 103 | 92% |
| Scientists | 8 | 7% |
| Science communicators (journalists, bloggers, editors) | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 408 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 408 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 50 | 12% |
| Student > Ph. D. Student | 43 | 11% |
| Student > Doctoral Student | 18 | 4% |
| Researcher | 16 | 4% |
| Lecturer | 16 | 4% |
| Other | 59 | 14% |
| Unknown | 206 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 61 | 15% |
| Engineering | 33 | 8% |
| Business, Management and Accounting | 28 | 7% |
| Economics, Econometrics and Finance | 25 | 6% |
| Unspecified | 10 | 2% |
| Other | 39 | 10% |
| Unknown | 212 | 52% |
Attention Score in Context
This research output has an Altmetric Attention Score of 69. 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 28 October 2023.
All research outputs
#637,945
of 25,936,091 outputs
Outputs from Frontiers in Business Research in China
#1
of 28 outputs
Outputs of similar age
#19,656
of 435,573 outputs
Outputs of similar age from Frontiers in Business Research in China
#1
of 1 outputs
Altmetric has tracked 25,936,091 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 28 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one scored the same or higher as 27 of them.
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 435,573 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 95% of its contemporaries.
We're also able to compare this research output to 1 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