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Abusive Language Detection in Online Conversations by Combining Content- and Graph-Based Features

Overview of attention for article published in arXiv, June 2019
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

twitter
6 X users

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
45 Mendeley
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Title
Abusive Language Detection in Online Conversations by Combining Content- and Graph-Based Features
Published in
arXiv, June 2019
DOI 10.3389/fdata.2019.00008
Pubmed ID
Authors

Noé Cécillon, Vincent Labatut, Richard Dufour, Georges Linarès

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 20%
Student > Ph. D. Student 7 16%
Student > Bachelor 6 13%
Researcher 5 11%
Professor > Associate Professor 2 4%
Other 2 4%
Unknown 14 31%
Readers by discipline Count As %
Computer Science 21 47%
Business, Management and Accounting 3 7%
Linguistics 3 7%
Engineering 2 4%
Social Sciences 1 2%
Other 1 2%
Unknown 14 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 06 June 2019.
All research outputs
#13,411,687
of 23,148,322 outputs
Outputs from arXiv
#213,326
of 952,387 outputs
Outputs of similar age
#169,852
of 352,411 outputs
Outputs of similar age from arXiv
#6,770
of 28,206 outputs
Altmetric has tracked 23,148,322 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 952,387 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 75% 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 352,411 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 28,206 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 74% of its contemporaries.