{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T16:24:43Z","timestamp":1775751883583,"version":"3.50.1"},"reference-count":45,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2018,2,5]],"date-time":"2018-02-05T00:00:00Z","timestamp":1517788800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["EL"],"published-print":{"date-parts":[[2018,2,5]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The study aims to showcase public sentiments via social media, Twitter, during 2014 floods of Jammu and Kashmir, India.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>The study is based on content analysis of tweets related to Kashmir floods. Search was performed with \u201c#kashmirfloods\u201d and was confined to tweets posted from 4 September 2014 through 3 November 2014. A naturalistic approach was applied to examine the content and classify tweets into 5 major and 25 sub categories. Data as such collected were tabulated in SPSS 21 for analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>During the study period, individuals, news channels, and organisations posted a total of 36,697 tweets related to Kashmir floods. It all started with an outburst of tweets which goes on declining (exponentially) with every passing day. People express themselves in a number of ways with informational tweets used more during the time of disaster. Individuals expressing their sentiments outscore other types of sentiments with text-based tweets ranking high. About 44 per cent of tweets were retweeted, and nearly 31 per cent tweets were marked favourite. Comparatively, more number of informational and help tweets were retweeted or marked favourite. Contextual richness of tweet (i.e. number of embedded expressions) enhances its visibility by means of getting liked and\/or retweeted. A statistically significant positive association is observed between the number of expressions in a tweet and the number of times it is liked (favourite) or retweeted.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title><jats:p>Twitter plays a pivotal role during natural calamities like Kashmir floods to connect people in the hour of need and help. It provides a platform where the plight of people is heard across the globe and which encourages people to unite and overcome hurdles together.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>This study examines the sentiments of people expressed during Jammu and Kashmir (India) Floods 2014 on social media \u2013 Twitter.<\/jats:p><\/jats:sec>","DOI":"10.1108\/el-12-2015-0244","type":"journal-article","created":{"date-parts":[[2017,12,29]],"date-time":"2017-12-29T19:24:28Z","timestamp":1514575468000},"page":"38-54","source":"Crossref","is-referenced-by-count":18,"title":["Twitter sentiments related to natural calamities"],"prefix":"10.1108","volume":"36","author":[{"given":"Sumeer","family":"Gul","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tariq 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