{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T09:44:30Z","timestamp":1780393470922,"version":"3.54.1"},"reference-count":46,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3119063","type":"journal-article","created":{"date-parts":[[2021,10,10]],"date-time":"2021-10-10T22:57:43Z","timestamp":1633906663000},"page":"141023-141035","source":"Crossref","is-referenced-by-count":21,"title":["Using a Hybrid-Classification Method to Analyze Twitter Data During Critical Events"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4044-9315","authenticated-orcid":false,"given":"Saadat M.","family":"Alhashmi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7957-7862","authenticated-orcid":false,"given":"Ahmed M.","family":"Khedr","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ifra","family":"Arif","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Magdi","family":"El Bannany","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.4018\/IJSWIS.2020010106"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s10791-008-9070-z"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557156"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2018.05.109"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/2063576.2063726"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1504\/IJSNM.2015.072280"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICTer.2012.6423033"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2007.05.028"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/KST.2013.6512800"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-18029-3_3"},{"key":"ref10","first-page":"132","article-title":"Mapping moods: Geo-mapped sentiment analysis during hurricane sandy","author":"caragea","year":"2014","journal-title":"Proc ISCRAM"},{"key":"ref40","first-page":"1","article-title":"Stance and influence of Twitter users regarding the brexit referendum","volume":"4","author":"gr?ar","year":"2017","journal-title":"Computer Netw s"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"919","DOI":"10.1109\/TKDE.2012.29","article-title":"Tweet analysis for real-time event detection and earthquake reporting system development","volume":"25","author":"sakaki","year":"2012","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijdrr.2019.101176"},{"key":"ref13","first-page":"220","article-title":"Opinion mining on Twitter: A sentiment analysis of the Iran deal","author":"abedin","year":"2018","journal-title":"Proc PACIS"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2018.8489703"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCIC.2016.7919608"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/IS3C.2018.00067"},{"key":"ref17","first-page":"520","article-title":"Codex: Combining an svm classifier and character n-gram language models for sentiment analysis on Twitter text","author":"han","year":"2013","journal-title":"Proc 2nd Joint Conf Lexical Comput Semantics SEM)"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.02.002"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.06.040"},{"key":"ref28","article-title":"Twitter sentiment classification using distant supervision","volume":"1","author":"go","year":"2009"},{"key":"ref4","author":"danneman","year":"2014","journal-title":"Social Media Mining with R Deploy"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/COMSNETS.2014.6734907"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.tele.2017.10.006","article-title":"Sentiment analysis on Twitter: A text mining approach to the Syrian refugee crisis","volume":"35","author":"\u00f6zt\u00fcrk","year":"2018","journal-title":"Telematics and Informatics"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.03.071"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4614-6880-6_28"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2017.02.004"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1047"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.01.005"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2018.01.051"},{"key":"ref9","author":"weick","year":"2015","journal-title":"Managing the Unexpected Sustained Performance in a Complex World"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1080\/08838151.2017.1344673"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.compenvurbsys.2018.09.002"},{"key":"ref20","first-page":"846","article-title":"A fine-grained sentiment analysis approach for detecting crisis related microposts","author":"schulz","year":"2013","journal-title":"Proc ISCRAM"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.2307\/2026705"},{"key":"ref22","article-title":"Tweet analysis for real-time event detection and earthquake reporting system development","volume":"4","author":"ekta","year":"2017","journal-title":"Int Res J Eng Technol"},{"key":"ref21","first-page":"1","article-title":"Crowd sentiment detection during disasters and crises","author":"nagy","year":"2012","journal-title":"Proc 9th Int ISCRAM Conf"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2923275"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2020.103265"},{"key":"ref41","first-page":"819","article-title":"Sentiment classification using machine learning techniques","volume":"5","author":"wawre","year":"2016","journal-title":"Int J Sci Res"},{"key":"ref23","first-page":"52","article-title":"Experimental evaluation of a lexicon-and corpus-based ensemble for multi-way sentiment analysis","author":"cao","year":"2012","journal-title":"Proc Australas Lang Technol Assoc Workshop"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCCNT45670.2019.8944513"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2020.108288"},{"key":"ref43","first-page":"54","article-title":"A comparison of domain-based word polarity estimation using different word embeddings","author":"pablos","year":"2016","journal-title":"Proc 10th Int Conf Lang Resour Eval (LREC)"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-017-3003-y"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09565914.pdf?arnumber=9565914","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:55:54Z","timestamp":1639770954000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9565914\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3119063","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}