Difference between revisions of "Estimating Tourism Statistics with Wikipedia Page Views"
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| + | {{Infobox work | ||
| + | | title = Estimating Tourism Statistics with Wikipedia Page Views | ||
| + | | date = 2015 | ||
| + | | authors = [[Christian M. Alis]]<br />[[Adrian Letchford]]<br />[[Tobias Preis]] | ||
| + | | doi = 10.1145/2786451.2786925 | ||
| + | | link = https://dl.acm.org/citation.cfm?doid=2786451.2786925 | ||
| + | }} | ||
'''Estimating Tourism Statistics with Wikipedia Page Views''' - scientific work related to [[Wikipedia quality]] published in 2015, written by [[Christian M. Alis]], [[Adrian Letchford]] and [[Tobias Preis]]. | '''Estimating Tourism Statistics with Wikipedia Page Views''' - scientific work related to [[Wikipedia quality]] published in 2015, written by [[Christian M. Alis]], [[Adrian Letchford]] and [[Tobias Preis]]. | ||
== Overview == | == Overview == | ||
Decision makers depend on socio-economic [[indicators]] to shape the world authors inhabit. Reports of these indicators are often delayed due to the effort involved in gathering and aggregating the underlying data. Authors increasing interactions with large scale technological systems are generating vast datasets on global human behaviour which are immediately accessible. Here authors analyse whether data on how often people view [[Wikipedia]] articles might help us to improve estimates of the current number of tourists leaving the UK. Authors analyses suggest that in the absence of sufficient history, Wikipedia page views provide an advantage. Authors conclude that when using adaptive models, Wikipedia usage opens up the possibility to improve estimates of tourism demand. | Decision makers depend on socio-economic [[indicators]] to shape the world authors inhabit. Reports of these indicators are often delayed due to the effort involved in gathering and aggregating the underlying data. Authors increasing interactions with large scale technological systems are generating vast datasets on global human behaviour which are immediately accessible. Here authors analyse whether data on how often people view [[Wikipedia]] articles might help us to improve estimates of the current number of tourists leaving the UK. Authors analyses suggest that in the absence of sufficient history, Wikipedia page views provide an advantage. Authors conclude that when using adaptive models, Wikipedia usage opens up the possibility to improve estimates of tourism demand. | ||
Revision as of 10:34, 5 June 2020
Authors | Christian M. Alis Adrian Letchford Tobias Preis |
|---|---|
Publication date | 2015 |
DOI | 10.1145/2786451.2786925 |
Links | Original |
Estimating Tourism Statistics with Wikipedia Page Views - scientific work related to Wikipedia quality published in 2015, written by Christian M. Alis, Adrian Letchford and Tobias Preis.
Overview
Decision makers depend on socio-economic indicators to shape the world authors inhabit. Reports of these indicators are often delayed due to the effort involved in gathering and aggregating the underlying data. Authors increasing interactions with large scale technological systems are generating vast datasets on global human behaviour which are immediately accessible. Here authors analyse whether data on how often people view Wikipedia articles might help us to improve estimates of the current number of tourists leaving the UK. Authors analyses suggest that in the absence of sufficient history, Wikipedia page views provide an advantage. Authors conclude that when using adaptive models, Wikipedia usage opens up the possibility to improve estimates of tourism demand.
