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Mapping auroral activity with Twitter

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Mapping auroral activity with Twitter. / Case, Nathan; MacDonald, Elizabeth ; Heavner, Matt et al.
In: Geophysical Research Letters, Vol. 42, No. 10, 28.05.2015, p. 3668-3676.

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Harvard

Case, N, MacDonald, E, Heavner, M, Tapia, A & Lalone, N 2015, 'Mapping auroral activity with Twitter', Geophysical Research Letters, vol. 42, no. 10, pp. 3668-3676. https://doi.org/10.1002/2015GL063709

APA

Case, N., MacDonald, E., Heavner, M., Tapia, A., & Lalone, N. (2015). Mapping auroral activity with Twitter. Geophysical Research Letters, 42(10), 3668-3676. https://doi.org/10.1002/2015GL063709

Vancouver

Case N, MacDonald E, Heavner M, Tapia A, Lalone N. Mapping auroral activity with Twitter. Geophysical Research Letters. 2015 May 28;42(10):3668-3676. Epub 2015 May 4. doi: 10.1002/2015GL063709

Author

Case, Nathan ; MacDonald, Elizabeth ; Heavner, Matt et al. / Mapping auroral activity with Twitter. In: Geophysical Research Letters. 2015 ; Vol. 42, No. 10. pp. 3668-3676.

Bibtex

@article{28e71fc7ecb840c5ad3a88bff3fd270b,
title = "Mapping auroral activity with Twitter",
abstract = "Twitter is a popular, publicly-accessible, social media service that has proven useful in mapping large-scale events in real-time. In this study, for the first time, the use of Twitter as a measure of auroral activity is investigated. Peaks in the number of aurora-related tweets are found to frequently coincide with geomagnetic disturbances (detection rate of 91%). Additionally, the number of daily aurora-related tweets is found to strongly correlate with several auroral strength proxies (ravg ≈ 0.7). An examination is made of the bias for location and time of day within Twitter data, and a first order correction of these effects is presented. Overall, the results suggest that Twitter can provide both specific details about an individual aurora and accurate real-time indication of when, and even from where, an aurora is visible.",
keywords = "aurora, mapping, Twitter, citizen science",
author = "Nathan Case and Elizabeth MacDonald and Matt Heavner and Andrea Tapia and Nicolas Lalone",
note = "Copyright 2015 American Geophysical Union.",
year = "2015",
month = may,
day = "28",
doi = "10.1002/2015GL063709",
language = "English",
volume = "42",
pages = "3668--3676",
journal = "Geophysical Research Letters",
issn = "0094-8276",
publisher = "John Wiley & Sons, Ltd",
number = "10",

}

RIS

TY - JOUR

T1 - Mapping auroral activity with Twitter

AU - Case, Nathan

AU - MacDonald, Elizabeth

AU - Heavner, Matt

AU - Tapia, Andrea

AU - Lalone, Nicolas

N1 - Copyright 2015 American Geophysical Union.

PY - 2015/5/28

Y1 - 2015/5/28

N2 - Twitter is a popular, publicly-accessible, social media service that has proven useful in mapping large-scale events in real-time. In this study, for the first time, the use of Twitter as a measure of auroral activity is investigated. Peaks in the number of aurora-related tweets are found to frequently coincide with geomagnetic disturbances (detection rate of 91%). Additionally, the number of daily aurora-related tweets is found to strongly correlate with several auroral strength proxies (ravg ≈ 0.7). An examination is made of the bias for location and time of day within Twitter data, and a first order correction of these effects is presented. Overall, the results suggest that Twitter can provide both specific details about an individual aurora and accurate real-time indication of when, and even from where, an aurora is visible.

AB - Twitter is a popular, publicly-accessible, social media service that has proven useful in mapping large-scale events in real-time. In this study, for the first time, the use of Twitter as a measure of auroral activity is investigated. Peaks in the number of aurora-related tweets are found to frequently coincide with geomagnetic disturbances (detection rate of 91%). Additionally, the number of daily aurora-related tweets is found to strongly correlate with several auroral strength proxies (ravg ≈ 0.7). An examination is made of the bias for location and time of day within Twitter data, and a first order correction of these effects is presented. Overall, the results suggest that Twitter can provide both specific details about an individual aurora and accurate real-time indication of when, and even from where, an aurora is visible.

KW - aurora

KW - mapping

KW - Twitter

KW - citizen science

U2 - 10.1002/2015GL063709

DO - 10.1002/2015GL063709

M3 - Journal article

VL - 42

SP - 3668

EP - 3676

JO - Geophysical Research Letters

JF - Geophysical Research Letters

SN - 0094-8276

IS - 10

ER -