{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:18:53Z","timestamp":1750220333748,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":46,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T00:00:00Z","timestamp":1656201600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,6,26]]},"DOI":"10.1145\/3501247.3531552","type":"proceedings-article","created":{"date-parts":[[2022,6,24]],"date-time":"2022-06-24T22:41:09Z","timestamp":1656110469000},"page":"327-335","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Multi-task Models for Multi-faceted Classification of Pandemic Information on Social Media"],"prefix":"10.1145","author":[{"given":"Xinchen","family":"Yu","sequence":"first","affiliation":[{"name":"Information Science, University of North Texas, USA"}]},{"given":"Zhuoli","family":"Xie","sequence":"additional","affiliation":[{"name":"TAMS, University of North Texas, USA"}]},{"given":"Afra","family":"Mashhadi","sequence":"additional","affiliation":[{"name":"Computing & Software Systems, University of Washington Bothell, USA"}]},{"given":"Lingzi","family":"Hong","sequence":"additional","affiliation":[{"name":"Information Science, University of North Texas, USA"}]}],"member":"320","published-online":{"date-parts":[[2022,6,26]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Proceedings of the 15th ISCRAM Conference.","author":"Aipe Alan","year":"2018","unstructured":"Alan Aipe , N Mukuntha , Asif Ekbal , and Sadao Kurohashi . 2018 . Deep learning approach towards multi-label classification of crisis related tweets . In Proceedings of the 15th ISCRAM Conference. Alan Aipe, N Mukuntha, Asif Ekbal, and Sadao Kurohashi. 2018. Deep learning approach towards multi-label classification of crisis related tweets. In Proceedings of the 15th ISCRAM Conference."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1099"},{"key":"e_1_3_2_2_3_1","volume-title":"Proceedings of the International AAAI Conference on Web and Social Media, Vol.\u00a012","author":"Alam Firoj","year":"2018","unstructured":"Firoj Alam , Ferda Ofli , and Muhammad Imran . 2018 . Crisismmd: Multimodal twitter datasets from natural disasters . In Proceedings of the International AAAI Conference on Web and Social Media, Vol.\u00a012 . Firoj Alam, Ferda Ofli, and Muhammad Imran. 2018. Crisismmd: Multimodal twitter datasets from natural disasters. In Proceedings of the International AAAI Conference on Web and Social Media, Vol.\u00a012."},{"key":"e_1_3_2_2_4_1","volume-title":"Proceedings of the International AAAI Conference on Web and Social Media, Vol.\u00a015","author":"Alam Firoj","year":"2021","unstructured":"Firoj Alam , Umair Qazi , Muhammad Imran , and Ferda Ofli . 2021 . HumAID: Human-Annotated Disaster Incidents Data from Twitter with Deep Learning Benchmarks . In Proceedings of the International AAAI Conference on Web and Social Media, Vol.\u00a015 . 933\u2013942. Firoj Alam, Umair Qazi, Muhammad Imran, and Ferda Ofli. 2021. HumAID: Human-Annotated Disaster Incidents Data from Twitter with Deep Learning Benchmarks. In Proceedings of the International AAAI Conference on Web and Social Media, Vol.\u00a015. 933\u2013942."},{"key":"e_1_3_2_2_5_1","volume-title":"Proceedings of the International AAAI Conference on Web and Social Media, Vol.\u00a015","author":"Alam Firoj","year":"2021","unstructured":"Firoj Alam , Hassan Sajjad , Muhammad Imran , and Ferda Ofli . 2021 . CrisisBench: Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing . In Proceedings of the International AAAI Conference on Web and Social Media, Vol.\u00a015 . 923\u2013932. Firoj Alam, Hassan Sajjad, Muhammad Imran, and Ferda Ofli. 2021. CrisisBench: Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing. In Proceedings of the International AAAI Conference on Web and Social Media, Vol.\u00a015. 923\u2013932."},{"volume-title":"International semantic web conference","author":"Burel Gr\u00e9goire","key":"e_1_3_2_2_6_1","unstructured":"Gr\u00e9goire Burel , Hassan Saif , and Harith Alani . 2017. Semantic wide and deep learning for detecting crisis-information categories on social media . In International semantic web conference . Springer , 138\u2013155. Gr\u00e9goire Burel, Hassan Saif, and Harith Alani. 2017. Semantic wide and deep learning for detecting crisis-information categories on social media. In International semantic web conference. Springer, 138\u2013155."},{"key":"e_1_3_2_2_7_1","volume-title":"International Conference on Information Systems for Crisis Response and Management. 137\u2013147","author":"Caragea Cornelia","year":"2016","unstructured":"Cornelia Caragea , Adrian Silvescu , and Andrea\u00a0 H Tapia . 2016 . Identifying informative messages in disaster events using convolutional neural networks . In International Conference on Information Systems for Crisis Response and Management. 137\u2013147 . Cornelia Caragea, Adrian Silvescu, and Andrea\u00a0H Tapia. 2016. Identifying informative messages in disaster events using convolutional neural networks. In International Conference on Information Systems for Crisis Response and Management. 137\u2013147."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cag.2013.10.008"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.2196\/19273"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390177"},{"key":"e_1_3_2_2_11_1","volume-title":"Local Individuals. In Proceedings of the Proceedings of 17th International Conference on Information Systems for Crisis Response and Management.","author":"Ann\u00a0St Denis Lise","year":"2020","unstructured":"Lise Ann\u00a0St Denis , Amanda\u00a0Lee Hughes , Jeremy Diaz , Kylen Solvik , Maxwell\u00a0 B Joseph , and Jennifer\u00a0 K Balch . 2020 . \u2018What I Need to Know is What I Don\u2019t Know!\u2019: Filtering Disaster Twitter Data for Information from Local Individuals. In Proceedings of the Proceedings of 17th International Conference on Information Systems for Crisis Response and Management. Lise Ann\u00a0St Denis, Amanda\u00a0Lee Hughes, Jeremy Diaz, Kylen Solvik, Maxwell\u00a0B Joseph, and Jennifer\u00a0K Balch. 2020. \u2018What I Need to Know is What I Don\u2019t Know!\u2019: Filtering Disaster Twitter Data for Information from Local Individuals. In Proceedings of the Proceedings of 17th International Conference on Information Systems for Crisis Response and Management."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2019.05.010"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3297001.3297030"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3091478.3091502"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487788.2488109"},{"key":"e_1_3_2_2_16_1","unstructured":"Muhammad Imran Prasenjit Mitra and Carlos Castillo. 2016. Twitter as a lifeline: human-annotated Twitter corpora for NLP of crisis-related messages. LREC.  Muhammad Imran Prasenjit Mitra and Carlos Castillo. 2016. Twitter as a lifeline: human-annotated Twitter corpora for NLP of crisis-related messages. LREC."},{"key":"e_1_3_2_2_17_1","volume-title":"Using AI and Social Media Multimodal Content for Disaster Response and Management: Opportunities, Challenges, and Future Directions. Information Processing & Management 57, 5","author":"Imran Muhammad","year":"2020","unstructured":"Muhammad Imran , Ferda Ofli , Doina Caragea , and Antonio Torralba . 2020. Using AI and Social Media Multimodal Content for Disaster Response and Management: Opportunities, Challenges, and Future Directions. Information Processing & Management 57, 5 ( 2020 ). Muhammad Imran, Ferda Ofli, Doina Caragea, and Antonio Torralba. 2020. Using AI and Social Media Multimodal Content for Disaster Response and Management: Opportunities, Challenges, and Future Directions. Information Processing & Management 57, 5 (2020)."},{"key":"e_1_3_2_2_18_1","volume-title":"Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets. JMIR infodemiology 1, 1","author":"Kahanek Alexander","year":"2021","unstructured":"Alexander Kahanek , Xinchen Yu , Lingzi Hong , Ana Cleveland , Jodi Philbrick , 2021. Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets. JMIR infodemiology 1, 1 ( 2021 ), e31671. Alexander Kahanek, Xinchen Yu, Lingzi Hong, Ana Cleveland, Jodi Philbrick, 2021. Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets. JMIR infodemiology 1, 1 (2021), e31671."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106458"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-emnlp.340"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2018.10.010"},{"volume-title":"Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings.","author":"P.","key":"e_1_3_2_2_22_1","unstructured":"Diederik\u00a0 P. Kingma and Jimmy Ba. 2015 . Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings. Diederik\u00a0P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2020.102284"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1113"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3465336.3475117"},{"key":"e_1_3_2_2_26_1","volume-title":"Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692(2019).","author":"Liu Yinhan","year":"2019","unstructured":"Yinhan Liu , Myle Ott , Naman Goyal , Jingfei Du , Mandar Joshi , Danqi Chen , Omer Levy , Mike Lewis , Luke Zettlemoyer , and Veselin Stoyanov . 2019 . Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692(2019). Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692(2019)."},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/2749461"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3184558.3188729"},{"key":"e_1_3_2_2_29_1","volume-title":"The 3rd National Computing Colleges Conference. York.","author":"Edward\u00a0Marius O\u2019Keefe Simon","year":"2018","unstructured":"Simon Edward\u00a0Marius O\u2019Keefe and Reem Mansour\u00a0M Alrashdi . 2018 . Deep learning and word embeddings for tweet classification for crisis response . In The 3rd National Computing Colleges Conference. York. Simon Edward\u00a0Marius O\u2019Keefe and Reem Mansour\u00a0M Alrashdi. 2018. Deep learning and word embeddings for tweet classification for crisis response. In The 3rd National Computing Colleges Conference. York."},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/2675133.2675242"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.01.084"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3079452.3079491"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10796-018-9844-9"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijdrr.2020.101584"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1080\/01463373.2015.1012219"},{"key":"e_1_3_2_2_36_1","volume-title":"International Conference on Machine Learning. PMLR, 9120\u20139132","author":"Standley Trevor","year":"2020","unstructured":"Trevor Standley , Amir Zamir , Dawn Chen , Leonidas Guibas , Jitendra Malik , and Silvio Savarese . 2020 . Which tasks should be learned together in multi-task learning? . In International Conference on Machine Learning. PMLR, 9120\u20139132 . Trevor Standley, Amir Zamir, Dawn Chen, Leonidas Guibas, Jitendra Malik, and Silvio Savarese. 2020. Which tasks should be learned together in multi-task learning?. In International Conference on Machine Learning. PMLR, 9120\u20139132."},{"key":"e_1_3_2_2_37_1","volume-title":"Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018)","author":"Stowe Kevin","year":"2018","unstructured":"Kevin Stowe , Martha Palmer , Jennings Anderson , Marina Kogan , Leysia Palen , Kenneth\u00a0 M Anderson , Rebecca Morss , Julie Demuth , and Heather Lazrus . 2018 . Developing and evaluating annotation procedures for twitter data during hazard events . In Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018) . 133\u2013143. Kevin Stowe, Martha Palmer, Jennings Anderson, Marina Kogan, Leysia Palen, Kenneth\u00a0M Anderson, Rebecca Morss, Julie Demuth, and Heather Lazrus. 2018. Developing and evaluating annotation procedures for twitter data during hazard events. In Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018). 133\u2013143."},{"key":"e_1_3_2_2_38_1","volume-title":"Proceedings of the International AAAI Conference on Web and Social Media, Vol.\u00a05. 385\u2013392","author":"Verma Sudha","year":"2011","unstructured":"Sudha Verma , Sarah Vieweg , William Corvey , Leysia Palen , James Martin , Martha Palmer , Aaron Schram , and Kenneth Anderson . 2011 . Natural language processing to the rescue? extracting\u201d situational awareness\u201d tweets during mass emergency . In Proceedings of the International AAAI Conference on Web and Social Media, Vol.\u00a05. 385\u2013392 . Sudha Verma, Sarah Vieweg, William Corvey, Leysia Palen, James Martin, Martha Palmer, Aaron Schram, and Kenneth Anderson. 2011. Natural language processing to the rescue? extracting\u201d situational awareness\u201d tweets during mass emergency. In Proceedings of the International AAAI Conference on Web and Social Media, Vol.\u00a05. 385\u2013392."},{"volume-title":"Situational awareness in mass emergency: A behavioral and linguistic analysis of microblogged communications. Ph.\u00a0D. Dissertation","author":"Vieweg Sarah\u00a0Elizabeth","key":"e_1_3_2_2_39_1","unstructured":"Sarah\u00a0Elizabeth Vieweg . 2012. Situational awareness in mass emergency: A behavioral and linguistic analysis of microblogged communications. Ph.\u00a0D. Dissertation . University of Colorado at Boulder. Sarah\u00a0Elizabeth Vieweg. 2012. Situational awareness in mass emergency: A behavioral and linguistic analysis of microblogged communications. Ph.\u00a0D. Dissertation. University of Colorado at Boulder."},{"key":"e_1_3_2_2_40_1","unstructured":"Congcong Wang and David Lillis. 2021. Multi-task transfer learning for finding actionable information from crisis-related messages on social media. arXiv preprint arXiv:2102.13395(2021).  Congcong Wang and David Lillis. 2021. Multi-task transfer learning for finding actionable information from crisis-related messages on social media. arXiv preprint arXiv:2102.13395(2021)."},{"key":"e_1_3_2_2_41_1","unstructured":"Congcong Wang Paul Nulty and David Lillis. 2021. Transformer-based Multi-task Learning for Disaster Tweet Categorisation. arXiv preprint arXiv:2110.08010(2021).  Congcong Wang Paul Nulty and David Lillis. 2021. Transformer-based Multi-task Learning for Disaster Tweet Categorisation. arXiv preprint arXiv:2110.08010(2021)."},{"key":"e_1_3_2_2_42_1","volume-title":"Analysis of Detection Models for Disaster-Related Tweets. Analysis of Detection Models for Disaster-Related Tweets","author":"Wiegmann Matti","year":"2020","unstructured":"Matti Wiegmann , Jens Kersten , Friederike Klan , Martin Potthast , and Benno Stein . 2020. Analysis of Detection Models for Disaster-Related Tweets. Analysis of Detection Models for Disaster-Related Tweets ( 2020 ), 872\u2013880. Matti Wiegmann, Jens Kersten, Friederike Klan, Martin Potthast, and Benno Stein. 2020. Analysis of Detection Models for Disaster-Related Tweets. Analysis of Detection Models for Disaster-Related Tweets (2020), 872\u2013880."},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICIS.2017.7959984"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3274464"},{"key":"e_1_3_2_2_45_1","volume-title":"Automatic identification of eyewitness messages on twitter during disasters. Information processing & management 57, 1","author":"Zahra Kiran","year":"2020","unstructured":"Kiran Zahra , Muhammad Imran , and Frank\u00a0 O Ostermann . 2020. Automatic identification of eyewitness messages on twitter during disasters. Information processing & management 57, 1 ( 2020 ), 102107. Kiran Zahra, Muhammad Imran, and Frank\u00a0O Ostermann. 2020. Automatic identification of eyewitness messages on twitter during disasters. Information processing & management 57, 1 (2020), 102107."},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3070203"}],"event":{"name":"WebSci '22: 14th ACM Web Science Conference 2022","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"location":"Barcelona Spain","acronym":"WebSci '22"},"container-title":["14th ACM Web Science Conference 2022"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3501247.3531552","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3501247.3531552","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:12:18Z","timestamp":1750191138000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3501247.3531552"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,26]]},"references-count":46,"alternative-id":["10.1145\/3501247.3531552","10.1145\/3501247"],"URL":"https:\/\/doi.org\/10.1145\/3501247.3531552","relation":{},"subject":[],"published":{"date-parts":[[2022,6,26]]},"assertion":[{"value":"2022-06-26","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}