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X Demographics
Mendeley readers
Attention Score in Context
| Title |
COVID-19 Related Sentiment Analysis Using State-of-the-Art Machine Learning and Deep Learning Techniques
|
|---|---|
| Published in |
Frontiers in Public Health, January 2022
|
| DOI | 10.3389/fpubh.2021.812735 |
| Pubmed ID | |
| Authors |
Zunera Jalil, Ahmed Abbasi, Abdul Rehman Javed, Muhammad Badruddin Khan, Mozaherul Hoque Abul Hasanat, Khalid Mahmood Malik, Abdul Khader Jilani Saudagar |
X Demographics
The data shown below were collected from the profiles of 3 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 | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 106 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 12 | 11% |
| Student > Bachelor | 8 | 8% |
| Student > Doctoral Student | 6 | 6% |
| Lecturer | 6 | 6% |
| Unspecified | 6 | 6% |
| Other | 10 | 9% |
| Unknown | 58 | 55% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 20 | 19% |
| Unspecified | 6 | 6% |
| Medicine and Dentistry | 5 | 5% |
| Business, Management and Accounting | 3 | 3% |
| Nursing and Health Professions | 3 | 3% |
| Other | 9 | 8% |
| Unknown | 60 | 57% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 01 February 2022.
All research outputs
#18,733,166
of 23,885,338 outputs
Outputs from Frontiers in Public Health
#5,783
of 11,758 outputs
Outputs of similar age
#356,113
of 507,330 outputs
Outputs of similar age from Frontiers in Public Health
#366
of 804 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,758 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
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 507,330 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 804 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.