{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T14:23:53Z","timestamp":1753885433419,"version":"3.41.2"},"reference-count":0,"publisher":"Inderscience Publishers","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJCSM"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1504\/ijcsm.2023.10055652","type":"journal-article","created":{"date-parts":[[2023,4,18]],"date-time":"2023-04-18T13:00:15Z","timestamp":1681822815000},"page":"95","source":"Crossref","is-referenced-by-count":0,"title":["COVID-19: machine learning methods applied for twitter sentiment analysis of Indians before, during and after lockdown"],"prefix":"10.1504","volume":"17","author":[{"given":"H.S.","family":"Hota","sequence":"first","affiliation":[]},{"given":"Nilesh","family":"Verma","sequence":"additional","affiliation":[]},{"given":"Dinesh K.","family":"Sharma","sequence":"additional","affiliation":[]}],"member":"378","container-title":["International Journal of Computing Science and Mathematics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.inderscienceonline.com\/doi\/full\/10.1504\/IJCSM.2023.10055652","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,18]],"date-time":"2023-04-18T13:00:16Z","timestamp":1681822816000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.inderscience.com\/link.php?id=10055652"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":0,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023]]}},"URL":"https:\/\/doi.org\/10.1504\/ijcsm.2023.10055652","relation":{},"ISSN":["1752-5055","1752-5063"],"issn-type":[{"type":"print","value":"1752-5055"},{"type":"electronic","value":"1752-5063"}],"subject":[],"published":{"date-parts":[[2023]]},"article-number":"10055652"}}