Abstract
Social media provides companies a new means of communication with their customers, which offers untapped potential for consumer satisfaction. In this paper, we aimed to examine the Twitter feeds of Shaw Communications in order to collect information concerning outages and get a feel for their customer satisfaction as a whole. This was done by using sentiment classification, keyword gathering, and various other analysis tools. We found that, overall, the customer satisfaction of Shaw Communications was fairly neutral and that the number of outages reported was unexpectedly high.
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References
S. BV, Canadian outages, http://canadianoutages.com/ [Online; Accessed 27 Sept 2017]
W. Chamlertwat, P. Bhattarakosol, T. Rungkasiri, C. Haruechaiyasak, Discovering consumer insight from twitter via sentiment analysis. J. Univ. Comput. Sci. 18(8), 973–992 (2012)
R. Clarke, Roger clarke’s web site, http://www.rogerclarke.com/II/OzI04.html#CIAP [Online; Accessed 23 Sept 2017]
S. Erevelles, S. Srinivasan, S. Rangel, Consumer satisfaction for internet service providers: an analysis of underlying processes. Inf. Technol. Manag. 4(1), 69–89 (2003)
FindInternet.ca, Findinternet, https://www.findinternet.ca/en/shop [Online; Accessed 3 Dec 2017]
J. Henrique, Get old tweets, https://github.com/Jefferson-Henrique/GetOldTweets-python.git [Online; Accessed 3 Oct 2017]
How the Naive Bayes classifier works in machine learning (2017), http://dataaspirant.com/2017/02/06/naive-bayes-classifier-machine-learning/ [Online; Accessed 28 Nov 2017]
InternetLiveStats.com, Internet live stats, http://www.internetlivestats.com/ [Online; Accessed 23 Sept 2017]
B.J. Jansen, M. Zhang, K. Sobel, A. Chowdury, Twitter power: tweets as electronic word of mouth. J. Am. Soc. Inf. Sci. Technol. 60(11), 2169–2188 (2009)
S. Loria, Textblob (2014), https://github.com/sloria/TextBlob
D. Maynard, M.A. Greenwood, Who cares about sarcastic tweets? Investigating the impact of sarcasm on sentiment analysis (2014), pp. 4238–4243
Ookla, Ookla: the definitive source for global Internet metrics, http://www.ookla.com/ [Online; Accessed 23 Sept 2017]
Ookla, Speedtest market report: Canada, http://www.speedtest.net/reports/canada/ [Online; Accessed 23 Sept 2017]
A. Pak, P. Paroubek, Twitter as a corpus for sentiment analysis and opinion mining, in Proceedings of LREC (2010), pp. 1320–1326
Shaw.ca, Hotspots - Shaw Go WiFi, https://www.shaw.ca/wifi/hotspots/ [Online; Accessed 3 Dec 2017]
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Cressy, S., Pham, B.L., Wright, H., Alhajj, R. (2019). Detecting Canadian Internet Satisfaction by Analyzing Twitter Accounts of Shaw Communications. In: Kaya, M., Alhajj, R. (eds) Influence and Behavior Analysis in Social Networks and Social Media. ASONAM 2018. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-02592-2_6
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DOI: https://doi.org/10.1007/978-3-030-02592-2_6
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