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Uncovering wireless blackspots using Twitter data
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Guo, Weisi and Zhang, Jie (2017) Uncovering wireless blackspots using Twitter data. Electronics Letters, 53 (12). pp. 814-816. ISSN 0013-5194.
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WRAP-uncovering-wireless-blackspots-Twitter-Guo-2017.pdf - Accepted Version - Requires a PDF viewer. Download (1598Kb) | Preview |
Official URL: https://doi.org/10.1049/el.2017.0409
Abstract
Blackspots are areas of poor signal coverage or service delivery that leads to customer complaints and loss in business revenue. Understanding their spatial-temporal patterns at a high resolution is important for interventions. Conventional methods such as customer helplines, drive-by testing, and network analysis tools often lack the real-time capability and spatial accuracy required. In this paper, we investigate the potential of utilizing geo-tagged Twitter data to uncover blackspots. Here, we apply lexicon and machine-learning natural language processing techniques to over 1.4 million Tweets in London to uncover blackspots for both pre-4G (2012) and post-4G (2016) roll out. It was found that long-term poor signal complaints make up the majority of complaints (86%) pre-4G roll out, but short-term network failure was responsible for most complaints (66%) post-4G roll out.
Item Type: | Journal Article | ||||||
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Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||
Library of Congress Subject Headings (LCSH): | Wireless communication systems -- Testing -- London (England), Twitter (Firm) | ||||||
Journal or Publication Title: | Electronics Letters | ||||||
Publisher: | Institution of Engineering and Technology | ||||||
ISSN: | 0013-5194 | ||||||
Official Date: | 8 June 2017 | ||||||
Dates: |
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Volume: | 53 | ||||||
Number: | 12 | ||||||
Page Range: | pp. 814-816 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Date of first compliant deposit: | 2 May 2017 | ||||||
Date of first compliant Open Access: | 11 January 2018 |
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