| Title |
Exploring big data traits and data quality dimensions for big data analytics application using partial least squares structural equation modelling
|
|---|---|
| Published in |
Journal of Big Data, March 2021
|
| DOI | 10.1186/s40537-021-00439-5 |
| Authors |
Muslihah Wook, Nor Asiakin Hasbullah, Norulzahrah Mohd Zainudin, Zam Zarina Abdul Jabar, Suzaimah Ramli, Noor Afiza Mat Razali, Nurhafizah Moziyana Mohd Yusop |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 103 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 11% |
| Student > Master | 7 | 7% |
| Lecturer | 6 | 6% |
| Student > Doctoral Student | 6 | 6% |
| Student > Bachelor | 5 | 5% |
| Other | 14 | 14% |
| Unknown | 54 | 52% |
| Readers by discipline | Count | As % |
|---|---|---|
| Business, Management and Accounting | 19 | 18% |
| Computer Science | 14 | 14% |
| Unspecified | 4 | 4% |
| Engineering | 3 | 3% |
| Mathematics | 2 | 2% |
| Other | 5 | 5% |
| Unknown | 56 | 54% |
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 24 March 2021.
All research outputs
#18,797,301
of 23,295,606 outputs
Outputs from Journal of Big Data
#269
of 351 outputs
Outputs of similar age
#320,565
of 428,960 outputs
Outputs of similar age from Journal of Big Data
#9
of 15 outputs
Altmetric has tracked 23,295,606 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 351 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one is in the 5th percentile – i.e., 5% 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 428,960 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.