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Event detection on Twitter by mapping unexpected changes in streaming data into a spatiotemporal lattice

Overview of attention for article published in IEEE Transactions on Big Data, January 2019
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About this Attention Score

  • Among the highest-scoring outputs from this source (#38 of 167)

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
8 Mendeley
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Title
Event detection on Twitter by mapping unexpected changes in streaming data into a spatiotemporal lattice
Published in
IEEE Transactions on Big Data, January 2019
DOI 10.1109/tbdata.2019.2948594
Authors

Zubair Shah, Adam G. Dunn

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 13%
Student > Master 1 13%
Student > Ph. D. Student 1 13%
Professor > Associate Professor 1 13%
Student > Bachelor 1 13%
Other 1 13%
Unknown 2 25%
Readers by discipline Count As %
Computer Science 3 38%
Unspecified 2 25%
Engineering 1 13%
Unknown 2 25%

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 27 October 2019.
All research outputs
#11,664,003
of 14,714,661 outputs
Outputs from IEEE Transactions on Big Data
#38
of 167 outputs
Outputs of similar age
#233,626
of 321,013 outputs
Outputs of similar age from IEEE Transactions on Big Data
#1
of 1 outputs
Altmetric has tracked 14,714,661 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 167 research outputs from this source. They receive a mean Attention Score of 1.5. This one has gotten more attention than average, scoring higher than 74% 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 321,013 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them