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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
Fast and accurate sentiment classification using an enhanced Naive Bayes
model
|
---|---|
Chapter number | 24 |
Book title |
Intelligent Data Engineering and Automated Learning – IDEAL 2013
|
Published in |
arXiv, May 2013
|
DOI | 10.1007/978-3-642-41278-3_24 |
Book ISBNs |
978-3-64-241277-6, 978-3-64-241278-3
|
Authors |
Vivek Narayanan, Ishan Arora, Arjun Bhatia |
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 % |
---|---|---|
India | 1 | 25% |
Unknown | 3 | 75% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 50% |
Science communicators (journalists, bloggers, editors) | 1 | 25% |
Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 348 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Brazil | 2 | <1% |
United States | 1 | <1% |
Unknown | 345 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 62 | 18% |
Student > Bachelor | 45 | 13% |
Student > Ph. D. Student | 42 | 12% |
Researcher | 14 | 4% |
Student > Postgraduate | 14 | 4% |
Other | 54 | 16% |
Unknown | 117 | 34% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 178 | 51% |
Engineering | 21 | 6% |
Business, Management and Accounting | 7 | 2% |
Mathematics | 4 | 1% |
Social Sciences | 3 | <1% |
Other | 14 | 4% |
Unknown | 121 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 26 November 2018.
All research outputs
#2,638,794
of 22,711,242 outputs
Outputs from arXiv
#46,784
of 930,878 outputs
Outputs of similar age
#23,548
of 195,063 outputs
Outputs of similar age from arXiv
#235
of 7,863 outputs
Altmetric has tracked 22,711,242 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 930,878 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 94% 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 195,063 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 87% of its contemporaries.
We're also able to compare this research output to 7,863 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.