| Title |
Exposing influence campaigns in the age of LLMs: a behavioral-based AI approach to detecting state-sponsored trolls
|
|---|---|
| Published in |
EPJ Data Science, October 2023
|
| DOI | 10.1140/epjds/s13688-023-00423-4 |
| Pubmed ID | |
| Authors |
Fatima Ezzeddine, Omran Ayoub, Silvia Giordano, Gianluca Nogara, Ihab Sbeity, Emilio Ferrara, Luca Luceri |
X Demographics
The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 3 | 20% |
| United States | 3 | 20% |
| Grenada | 1 | 7% |
| Germany | 1 | 7% |
| United Kingdom | 1 | 7% |
| Unknown | 6 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 73% |
| Scientists | 3 | 20% |
| Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 21% |
| Other | 2 | 14% |
| Student > Bachelor | 1 | 7% |
| Lecturer | 1 | 7% |
| Student > Master | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 5 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 21% |
| Engineering | 2 | 14% |
| Biochemistry, Genetics and Molecular Biology | 1 | 7% |
| Agricultural and Biological Sciences | 1 | 7% |
| Arts and Humanities | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 6 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 10 March 2024.
All research outputs
#3,623,846
of 25,732,188 outputs
Outputs from EPJ Data Science
#262
of 457 outputs
Outputs of similar age
#58,167
of 360,804 outputs
Outputs of similar age from EPJ Data Science
#7
of 16 outputs
Altmetric has tracked 25,732,188 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 457 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.1. This one is in the 42nd percentile – i.e., 42% 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 360,804 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 83% of its contemporaries.
We're also able to compare this research output to 16 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 56% of its contemporaries.