2016
DOI: 10.1108/imds-10-2015-0417
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Insight from the horsemeat scandal

Abstract: Purpose – Social media has become an important part of daily interpersonal communication in contemporary society. The purpose of this paper is to explore the attitudes of UK consumers by identifying the hidden information in tweets, and provide a framework which can assist industry practitioners in managing social media data. Design/methodology/approach – Using a large-scale dataset of tweets relating to the Horsemeat scandal of 2013, a … Show more

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Cited by 40 publications
(20 citation statements)
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“…A frequency table of keywords was generated simultaneously. Thirdly, the co-occurrences of high frequency keywords were evaluated, and the main discussion themes were identified by clustered groups, then a Multidimensional Scaling (MDS) diagram was created (Tse et al, 2016). Fourthly, to investigate the large volume of opinions made by customers towards Tesco during the horsemeat scandal, a machine learning technique was adopted to classify customers' comments into the relevant discussion theme.…”
Section: Frameworkmentioning
confidence: 99%
See 4 more Smart Citations
“…A frequency table of keywords was generated simultaneously. Thirdly, the co-occurrences of high frequency keywords were evaluated, and the main discussion themes were identified by clustered groups, then a Multidimensional Scaling (MDS) diagram was created (Tse et al, 2016). Fourthly, to investigate the large volume of opinions made by customers towards Tesco during the horsemeat scandal, a machine learning technique was adopted to classify customers' comments into the relevant discussion theme.…”
Section: Frameworkmentioning
confidence: 99%
“…The MDS approach is a useful tool for identifying potential themes for focus in a discussion group (Tse et al 2016). In Figure 3, the bubble represents important dataset keywords and lines between keywords represent the strength of their relationships to each other.…”
Section: Multidimensional Scaling (Mds)mentioning
confidence: 99%
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