Information for a Better World: Shaping the Global Future
Springer International Publishing
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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Testing the Generalization of Neural Language Models for COVID-19 Misinformation Detection
|
|---|---|
| Book title |
Information for a Better World: Shaping the Global Future
|
| Published in |
arXiv, February 2022
|
| DOI | 10.1007/978-3-030-96957-8_33 |
| Book ISBNs |
978-3-03-096956-1, 978-3-03-096957-8
|
| Authors |
Jan Philip Wahle, Nischal Ashok, Terry Ruas, Norman Meuschke, Tirthankar Ghosal, Bela Gipp, Wahle, Jan Philip, Ashok, Nischal, Ruas, Terry, Meuschke, Norman, Ghosal, Tirthankar, Gipp, Bela |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 20% |
| Researcher | 2 | 10% |
| Other | 1 | 5% |
| Lecturer | 1 | 5% |
| Student > Doctoral Student | 1 | 5% |
| Other | 5 | 25% |
| Unknown | 6 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 45% |
| Business, Management and Accounting | 1 | 5% |
| Unspecified | 1 | 5% |
| Social Sciences | 1 | 5% |
| Medicine and Dentistry | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 7 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 13 November 2022.
All research outputs
#14,393,409
of 23,511,526 outputs
Outputs from arXiv
#262,092
of 972,877 outputs
Outputs of similar age
#209,799
of 443,095 outputs
Outputs of similar age from arXiv
#9,310
of 35,965 outputs
Altmetric has tracked 23,511,526 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 972,877 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 70% 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 443,095 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 35,965 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.