{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T19:31:26Z","timestamp":1775590286974,"version":"3.50.1"},"reference-count":78,"publisher":"Emerald","issue":"6","license":[{"start":{"date-parts":[[2016,7,11]],"date-time":"2016-07-11T00:00:00Z","timestamp":1468195200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,7,11]]},"abstract":"<jats:sec>\n               <jats:title content-type=\"abstract-heading\">Purpose<\/jats:title>\n               <jats:p> \u2013 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. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title>\n               <jats:p> \u2013 Using a large-scale dataset of tweets relating to the Horsemeat scandal of 2013, a comprehensive data analysis framework, which comprises multidimensional scaling and sentiment analysis, alongside other methods, was applied to explore customers\u2019 opinions. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Findings<\/jats:title>\n               <jats:p> \u2013 Making jokes in social media was a main trend in the tweets relating to Tesco during the Horsemeat scandal. Consumer sentiments were overall negative and burgers were the most mentioned product in the week-long period after the story broke. The posting of tweets was correlated with the timing of news coverage, which indicates that the traditional media is still crucial to public opinion formation. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title>\n               <jats:p> \u2013 This paper presents a progressive tweet-mining framework that can serve as a tool for academia and practitioners in crisis management. The proposed framework indicates the significant importance of timely categorising the topics, identifying the sentiment of tweets and understanding the changes of consumer opinions over time in a crisis. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title>\n               <jats:p> \u2013 The research presented in this paper is one of the limited social media research to focus on a UK food fraud issue and adds to the limited body of literature investigating consumer social media use from the side of industry practitioners.<\/jats:p>\n            <\/jats:sec>","DOI":"10.1108\/imds-10-2015-0417","type":"journal-article","created":{"date-parts":[[2016,6,29]],"date-time":"2016-06-29T14:48:49Z","timestamp":1467211729000},"page":"1178-1200","source":"Crossref","is-referenced-by-count":38,"title":["Insight from the horsemeat scandal"],"prefix":"10.1108","volume":"116","author":[{"given":"Ying Kei","family":"Tse","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minhao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bob","family":"Doherty","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paul","family":"Chappell","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philip","family":"Garnett","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2020121423070110600_b1","doi-asserted-by":"crossref","unstructured":"Agnihotri, R.\n               , \n                  Kothandaraman, P.\n               , \n                  Kashyap, R.\n                and \n                  Singh, R.\n                (2012), 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