{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T13:16:43Z","timestamp":1775567803507,"version":"3.50.1"},"reference-count":70,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,12,17]],"date-time":"2022-12-17T00:00:00Z","timestamp":1671235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,12,17]],"date-time":"2022-12-17T00:00:00Z","timestamp":1671235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,17]]},"DOI":"10.1109\/bigdata55660.2022.10020594","type":"proceedings-article","created":{"date-parts":[[2023,1,26]],"date-time":"2023-01-26T14:35:23Z","timestamp":1674743723000},"page":"4824-4832","source":"Crossref","is-referenced-by-count":4,"title":["An Empirical Study on Characterizing Natural Disasters in Class Imbalanced Social Media Data using Weak Supervision"],"prefix":"10.1109","author":[{"given":"Ramya","family":"Tekumalla","sequence":"first","affiliation":[{"name":"Georgia State University,Department of Computer Science,Atlanta,USA"}]},{"given":"Juan M.","family":"Banda","sequence":"additional","affiliation":[{"name":"Georgia State University,Department of Computer Science,Atlanta,USA"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocw028"},{"key":"ref57","article-title":"2020 US presidential election tweet IDs release 1.3","author":"chen","year":"2021"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/BF00116829"},{"key":"ref56","article-title":"BlackLivesMatter tweets","year":"2016"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/0020-0190(96)00006-3"},{"key":"ref59","article-title":"Twitter as a lifeline: Human-annotated twitter corpora for NLP of crisis-related messages","author":"imran","year":"2016"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.5808\/GI.2020.18.2.e16"},{"key":"ref58","article-title":"Tweets to donald trump (@realDonaldTrump)","author":"ruest","year":"2017"},{"key":"ref53","article-title":"115th U.S. congress tweet ids","author":"littman","year":"2017"},{"key":"ref52","article-title":"Twitter event datasets (2012-2016)","author":"zubiaga","year":"2017"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-019-00552-1"},{"key":"ref55","article-title":"Insight4news irish news related hashtagged tweet collection","author":"poghosyan","year":"2019"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-demo.40"},{"key":"ref54","article-title":"Immigration and travel ban tweet ids","author":"littman","year":"2018"},{"key":"ref17","article-title":"Hurricanes harvey and irma tweet ids","author":"littman","year":"2017"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1006\/jcss.1996.0019"},{"key":"ref19","article-title":"Twitter earthquake detection: earthquake monitoring in a social world","volume":"54","author":"earle","year":"2011","journal-title":"Annales de Geophysique"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1002\/meet.2014.14505101162"},{"key":"ref51","article-title":"Charlottesville tweet ids","author":"littman","year":"2018"},{"key":"ref50","article-title":"Dallas police shooting twitter dataset","author":"phillips","year":"2016"},{"key":"ref46","article-title":"U.S. government tweet ids","author":"littman","year":"2017"},{"key":"ref45","article-title":"#WomensMarch tweets","author":"ruest","year":"2017"},{"key":"ref48","article-title":"Nipsey hussle tweets","author":"omowale","year":"0"},{"key":"ref47","article-title":"End of term 2016 u.s. government twitter archive","author":"littman","year":"2017"},{"key":"ref42","article-title":"Healthcare tweet ids","author":"littman","year":"2019"},{"key":"ref41","article-title":"Trump tweet IDs","year":"0"},{"key":"ref44","article-title":"News outlet tweet ids","author":"littman","year":"2017"},{"key":"ref43","article-title":"2018 U.S. congressional election tweet ids","author":"wrubel","year":"2018"},{"key":"ref49","article-title":"Winter olympics 2018 tweet ids","author":"littman","year":"2018"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.271"},{"key":"ref7","first-page":"235","article-title":"Simultaneous object detection and ranking with weak supervision","volume":"23","author":"blaschko","year":"2010","journal-title":"Advances in neural information processing systems"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3329486.3329492"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-021-06614-2"},{"key":"ref3","article-title":"Weak supervision: the new programming paradigm for machine learning","author":"ratner","year":"2019","journal-title":"Hazy Research"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052611"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-11012-3"},{"key":"ref40","article-title":"Climate change tweets ids","author":"littman","year":"2019"},{"key":"ref35","article-title":"Hurricane dorian tweet IDs","author":"rachunok","year":"2019"},{"key":"ref34","article-title":"Hurricane harvey twitter dataset","author":"phillips","year":"2018"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0145406"},{"key":"ref36","article-title":"Hurricane dorian twitter dataset","author":"phillips","year":"2019"},{"key":"ref31","article-title":"Eclipse tweet IDs","year":"0"},{"key":"ref30","article-title":"2016 united states presidential election tweet ids","author":"littman","year":"2016"},{"key":"ref33","article-title":"Hurricane florence twitter dataset","author":"phillips","year":"2018"},{"key":"ref32","article-title":"Hurricane florence","author":"wrubel","year":"2019"},{"key":"ref2","article-title":"Learning from the crowd: Collaborative filtering techniques for identifying on-the-ground twitterers during mass disruptions","author":"starbird","year":"2012","journal-title":"ISCRAM"},{"key":"ref1","article-title":"A twitter tale of three hurricanes: Harvey, irma, and maria","author":"alam","year":"2018"},{"key":"ref39","article-title":"Beyond the hashtags twitter data","author":"freelon","year":"0"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/2998181.2998353"},{"key":"ref70","doi-asserted-by":"crossref","first-page":"1532","DOI":"10.3115\/v1\/D14-1162","article-title":"Glove: Global vectors for word representation","author":"pennington","year":"2014","journal-title":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/SIU.2015.7130033"},{"key":"ref68","article-title":"Hugging-Face&#x2019;s transformers: State-of-the-art natural language processing","author":"wolf","year":"2019"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1080\/15230406.2017.1356242"},{"key":"ref67","article-title":"simpletransformers","author":"rajapakse","year":"2019"},{"key":"ref26","article-title":"The internet archive","author":"machine","year":"2015"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/2675133.2675242"},{"key":"ref69","first-page":"150","article-title":"Text classification algorithms: A survey","volume":"10","author":"kowsari","year":"2019","journal-title":"Information An International Interdisciplinary Journal"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1287\/educ.1120.0105"},{"key":"ref64","article-title":"Disaster_tweet_bert","author":"nguyen","year":"0"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-demos.2"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2020.03.395"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/icwsm.v11i1.14950"},{"key":"ref65","first-page":"2042","article-title":"Convolutional neural network architectures for matching natural language sentences","volume":"27","author":"hu","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref28","article-title":"Puerto rico tweets","year":"2017"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/BigData55660.2022.10020214"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s13278-014-0163-y"},{"key":"ref60","first-page":"2825","article-title":"Scikit-learn: Machine learning in python","volume":"12","author":"pedregosa","year":"2011","journal-title":"Journal of Machine Learning Research JMLR"},{"key":"ref62","article-title":"RoBERTa: A robustly optimized BERT pretraining approach","author":"liu","year":"2019"},{"key":"ref61","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2018"}],"event":{"name":"2022 IEEE International Conference on Big Data (Big Data)","location":"Osaka, Japan","start":{"date-parts":[[2022,12,17]]},"end":{"date-parts":[[2022,12,20]]}},"container-title":["2022 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10020192\/10020156\/10020594.pdf?arnumber=10020594","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T17:08:40Z","timestamp":1676912920000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10020594\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,17]]},"references-count":70,"URL":"https:\/\/doi.org\/10.1109\/bigdata55660.2022.10020594","relation":{},"subject":[],"published":{"date-parts":[[2022,12,17]]}}}