{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T21:36:56Z","timestamp":1773524216233,"version":"3.50.1"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030157418","type":"print"},{"value":"9783030157425","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-15742-5_42","type":"book-chapter","created":{"date-parts":[[2019,3,12]],"date-time":"2019-03-12T03:02:45Z","timestamp":1552359765000},"page":"436-443","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Spatiotemporal Analysis on Sentiments and Retweet Patterns of Tweets for Disasters"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7410-8901","authenticated-orcid":false,"given":"Sijing","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9572-6709","authenticated-orcid":false,"given":"Jin","family":"Mao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,3,13]]},"reference":[{"issue":"4","key":"42_CR1","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1145\/2771588","volume":"47","author":"M Imran","year":"2015","unstructured":"Imran, M., Castillo, C., Diaz, F., et al.: Processing social media messages in mass emergency: a survey. ACM Comput. Surv. (CSUR) 47(4), 67 (2015)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"42_CR2","doi-asserted-by":"crossref","unstructured":"Cobo, A., Parra, D., Nav\u00f3n, J.: Identifying relevant messages in a twitter-based citizen channel for natural disaster situations. In: Proceedings of the 24th International Conference on World Wide Web, pp. 1189\u20131194 (2015)","DOI":"10.1145\/2740908.2741719"},{"key":"42_CR3","unstructured":"Vieweg, S.E.: Situational awareness in mass emergency: a behavioral and linguistic analysis of microblogged communications. University of Colorado at Boulder (2012)"},{"key":"42_CR4","doi-asserted-by":"crossref","unstructured":"Boyd D., Golder S., Lotan G.: Tweet, tweet, retweet: conversational aspects of retweeting on twitter. In: Proceedings of the 43rd Hawaii International Conference on System Sciences, pp. 1\u201310 (2010)","DOI":"10.1109\/HICSS.2010.412"},{"key":"42_CR5","doi-asserted-by":"crossref","unstructured":"Suh, B., Hong, L., Pirolli, P., Chi, E.H.: Want to be retweeted? Large scale analytics on factors impacting retweet in twitter network. In: Proceedings of IEEE Second International Conference on Social Computing, pp. 177\u2013184 (2010)","DOI":"10.1109\/SocialCom.2010.33"},{"key":"42_CR6","unstructured":"Pervin, N., Takeda, H., Toriumi, F.: Factors affecting retweetability: an event-centric analysis on Twitter. In: Proceedings of Thirty Fifth International Conference on Information Systems, pp. 1\u201310 (2014)"},{"issue":"3","key":"42_CR7","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1080\/01292986.2017.1290124","volume":"27","author":"L Zhang","year":"2017","unstructured":"Zhang, L., Xu, L., Zhang, W.: Social media as amplification station: factors that influence the speed of online public response to health emergencies. Asian J. Commun. 27(3), 322\u2013338 (2017)","journal-title":"Asian J. Commun."},{"key":"42_CR8","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1016\/j.ijdrr.2016.12.011","volume":"21","author":"VK Neppalli","year":"2017","unstructured":"Neppalli, V.K., Caragea, C., Squicciarini, A., et al.: Sentiment analysis during Hurricane Sandy in emergency response. Int. J. Disaster Risk Reduct. 21, 213\u2013222 (2017)","journal-title":"Int. J. Disaster Risk Reduct."},{"key":"42_CR9","unstructured":"Phillips, M.E.: Hurricane Harvey Twitter Dataset. \n                      https:\/\/digital.library.unt.edu\/ark:\/67531\/metadc993940\/\n                      \n                    . Accessed 22 Nov 2017"},{"issue":"2","key":"42_CR10","doi-asserted-by":"publisher","first-page":"e117288","DOI":"10.1371\/journal.pone.0117288","volume":"10","author":"Y Kryvasheyeu","year":"2015","unstructured":"Kryvasheyeu, Y., Chen, H., Moro, E., et al.: Performance of social network sensors during Hurricane Sandy. PLoS ONE 10(2), e117288 (2015)","journal-title":"PLoS ONE"},{"key":"42_CR11","unstructured":"Texas Hurricane Harvey (DR-4332). \n                      https:\/\/www.fema.gov\/disaster\/4332\n                      \n                    . Accessed 5 Mar 2018"},{"key":"42_CR12","unstructured":"Louisiana Tropical Storm Harvey (DR-4345). \n                      https:\/\/www.fema.gov\/disaster\/4345\n                      \n                    . Accessed 5 Mar 2018"},{"key":"42_CR13","unstructured":"Powell, J.W.: An introduction to the natural history of disaster. University of Maryland: Disaster Research Project (1954)"},{"key":"42_CR14","doi-asserted-by":"crossref","unstructured":"Kogan, M., Palen, L., Anderson, K.M.: Think local, retweet global: retweeting by the geographically-vulnerable during Hurricane Sandy. In: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work and Social Computing, pp. 981\u2013993 (2015)","DOI":"10.1145\/2675133.2675218"},{"issue":"1","key":"42_CR15","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1016\/j.tele.2017.10.006","volume":"35","author":"N Ozturk","year":"2018","unstructured":"Ozturk, N., Ayvaz, S.: Sentiment analysis on Twitter: a text mining approach to the Syrian refugee crisis. Telemat. Inform. 35(1), 136\u2013147 (2018)","journal-title":"Telemat. Inform."},{"issue":"12","key":"42_CR16","doi-asserted-by":"publisher","first-page":"2544","DOI":"10.1002\/asi.21416","volume":"61","author":"M Thelwall","year":"2010","unstructured":"Thelwall, M., Buckley, K., Paltoglou, G., et al.: Sentiment strength detection in short informal text. J. Am. Soc. Inform. Sci. Technol. 61(12), 2544\u20132558 (2010)","journal-title":"J. Am. Soc. Inform. Sci. Technol."},{"issue":"1","key":"42_CR17","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1002\/asi.21662","volume":"63","author":"M Thelwall","year":"2012","unstructured":"Thelwall, M., Buckley, K., Paltoglou, G., et al.: Sentiment in Twitter events. J. Am. Soc. Inf. Sci. Technol. 63(1), 163\u2013173 (2012)","journal-title":"J. Am. Soc. Inf. Sci. Technol."},{"key":"42_CR18","unstructured":"SentiStrength. \n                      http:\/\/sentistrength.wlv.ac.uk\/\n                      \n                    . Accessed 20 Mar 2018"},{"key":"42_CR19","doi-asserted-by":"crossref","unstructured":"Tsugawa, S., Ohsaki, H.: Negative messages spread rapidly and widely on social media. In: Proceedings of the 2015 ACM on Conference on Online Social Networks, pp. 151\u2013160 (2015)","DOI":"10.1145\/2817946.2817962"},{"key":"42_CR20","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/j.chb.2015.11.040","volume":"56","author":"R Gaspar","year":"2016","unstructured":"Gaspar, R., Pedro, C., Panagiotopoulos, P., et al.: Beyond positive or negative: qualitative sentiment analysis of social media reactions to unexpected stressful events. Comput. Hum. Behav. 56, 179\u2013191 (2016)","journal-title":"Comput. Hum. Behav."},{"issue":"4","key":"42_CR21","doi-asserted-by":"publisher","first-page":"217","DOI":"10.2753\/MIS0742-1222290408","volume":"29","author":"S Stieglitz","year":"2013","unstructured":"Stieglitz, S., Dang-Xuan, L.: Emotions and information diffusion in social media\u2014sentiment of microblogs and sharing behavior. J. Manag. Inf. Syst. 29(4), 217\u2013248 (2013)","journal-title":"J. Manag. Inf. Syst."},{"issue":"3","key":"42_CR22","doi-asserted-by":"publisher","first-page":"e1500779","DOI":"10.1126\/sciadv.1500779","volume":"2","author":"Y Kryvasheyeu","year":"2016","unstructured":"Kryvasheyeu, Y., Chen, H., Obradovich, N., et al.: Rapid assessment of disaster damage using social media activity. Sci. Adv. 2(3), e1500779 (2016)","journal-title":"Sci. Adv."},{"key":"42_CR23","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1016\/j.jom.2016.05.007","volume":"45","author":"E Yoo","year":"2016","unstructured":"Yoo, E., Rand, W., Eftekhar, M., et al.: Evaluating information diffusion speed and its determinants in social media networks during humanitarian crises. J. Oper. Manag. 45, 123\u2013133 (2016)","journal-title":"J. Oper. Manage."}],"container-title":["Lecture Notes in Computer Science","Information in Contemporary Society"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-15742-5_42","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,20]],"date-time":"2019-05-20T08:43:41Z","timestamp":1558341821000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-15742-5_42"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030157418","9783030157425"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-15742-5_42","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"13 March 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"iConference","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Information","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Washington, DC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 March 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 April 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconference2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ischools.org\/the-iconference\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"ConfTool","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"133","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"44","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"33","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"33% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"-","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"88 short papers were submitted in addition to the 133 full papers.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}