Detecting crisis events from unstructured text data using signal words as crisis determinants

References

• Alam, Firoj, Shafiq Joty, and Muhammad Imran. 2018. “Domain Adaptation with Adversarial Training and Graph Embeddings.” arXiv, arXiv:1805.05151, preprint.
   Google Scholar
• Alam, Firoj, 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. 15, 923–932, PKP Publishing Services Network.
   Google Scholar
• Albeverio, Sergio, Volker Jentsch, and Holger Kantz. 2006. Extreme Events in Nature and Society. Springer Science & Business Media.
   Google Scholar
• AlKhwiter, Wasan, and Nora Al-Twairesh. 2021. “Part-of-Speech Tagging for Arabic Tweets Using CRF and Bi-LSTM.” Computer Speech & Language 65:101–138. https://doi.org/10.1016/j.csl.2020.101138.
   Web of Science ®Google Scholar
• Alomari, Ebtesam, Rashid Mehmood, and Iyad Katib. 2019. “Road Traffic Event Detection using Twitter Data, Machine Learning, and Apache Spark.” In 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), 1888–1895. IEEE.
   Google Scholar
• Al Omran, Fouad Nasser A., and Christoph Treude. 2017. “Choosing an NLP Library for Analyzing Software Documentation: A Systematic Literature Review and a Series of Experiments.” In 2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR), 187–197. IEEE.
   Google Scholar
• Behl, Shivam, Aman Rao, Sahil Aggarwal, Sakshi Chadha, and H. S. Pannu. 2021. “Twitter for Disaster Relief Through Sentiment Analysis for COVID-19 and Natural Hazard Crises.” International Journal of Disaster Risk Reduction 55:102101. https://doi.org/10.1016/j.ijdrr.2021.102101.
   Web of Science ®Google Scholar
• Bosch, Harald, Dennis Thom, Florian Heimerl, Edwin Püttmann, Steffen Koch, Robert Krüger, Michael Wörner, and Thomas Ertl. 2013. “ScatterBlogs2: Real-time Monitoring of Microblog Messages Through User-guided Filtering.” IEEE Transactions on Visualization and Computer Graphics19 (12): 2022–2031. https://doi.org/10.1109/TVCG.2013.186.
   PubMed Web of Science ®Google Scholar
• Bouadjenek, Mohamed Reda, and Scott Sanner. 2019. “Relevance-driven Clustering for Visual Information Retrieval on Twitter.” In Proceedings of the 2019 Conference on Human Information Interaction and Retrieval, 349–353. New York: ACM.
   Google Scholar
• Chakrabarti, Deepayan, and Kunal Punera. 2011. “Event Summarization using Tweets.” In Proceedings of the International AAAI Conference on Web and Social Media. Vol. 5, 66–73. Barcelona, Catalonia, Spain: PKP Publishing Services Network.
   Google Scholar
• Dabiri, Sina, and Kevin Heaslip. 2019. “Developing a Twitter-based Traffic Event Detection Model Using Deep Learning Architectures.” Expert Systems with Applications 118:425–439. https://doi.org/10.1016/j.eswa.2018.10.017.
   Web of Science ®Google Scholar
• de Bruijn, Jens A., Hans de Moel, Brenden Jongman, Marleen C. de Ruiter, Jurjen Wagemaker, and Jeroen C. J. H. Aerts. 2019. “A Global Database of Historic and Real-time Flood Events Based on Social Media.” Scientific Data 6 (1): 311. https://doi.org/10.1038/s41597-019-0326-9.
   PubMed Web of Science ®Google Scholar
• Gimpel, Kevin, Nathan Schneider, Brendan O'Connor, Dipanjan Das, Daniel Mills, Jacob Eisenstein, Michael Heilman, et al. 2010. Part-of-speech Tagging for Twitter: Annotation, Features, and Experiments. Technical Report. Carnegie-Mellon Univ Pittsburgh Pa School of Computer Science.
   Google Scholar
• Gu, Yiming, Zhen (Sean) Qian, and Feng Chen. 2016. “From Twitter to Detector: Real-time Traffic Incident Detection Using Social Media Data.” Transportation Research Part C: Emerging Technologies67:321–342. https://doi.org/10.1016/j.trc.2016.02.011.
   Web of Science ®Google Scholar
• HaCohen-Kerner, Yaakov, Daniel Miller, and Yair Yigal. 2020. “The Influence of Preprocessing on Text Classification Using a Bag-of-words Representation.” PLoS ONE 15 (5): e0232525. https://doi.org/10.1371/journal.pone.0232525.
   PubMed Web of Science ®Google Scholar
• Hagras, Mohamed, Ghada Hassan, and Nadine Farag. 2017. “Towards Natural Disasters Detection from Twitter Using Topic Modelling.” In 2017 European Conference on Electrical Engineering and Computer Science (EECS), 272–279. Bern, Switzerland: IEEE.
   Google Scholar
• Halterman, Andrew. 2017. “Mordecai: Full Text Geoparsing and Event Geocoding.” Journal of Open Source Software 2 (9): 91. https://doi.org/10.21105/joss.
   Google Scholar
• Imran, Muhammad, Prasenjit Mitra, and Carlos Castillo. 2016. “Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messages.” arXiv, arXiv:1605.05894, preprint.
   Google Scholar
• Interdonato, Roberto, Jean-Loup Guillaume, and Antoine Doucet. 2019. “A Lightweight and Multilingual Framework for Crisis Information Extraction From Twitter Data.” Social Network Analysis and Mining 9 (1): 1–20. https://doi.org/10.1007/s13278-019-0608-4.
   Web of Science ®Google Scholar
• Kejriwal, Mayank, and Peilin Zhou. 2019. “SAVIZ: Interactive Exploration and Visualization of Situation Labeling Classifiers Over Crisis Social Media Data.” In Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 705–708. New York: Association for Computing Machinery.
   Google Scholar
• Khare, Prashant, Miriam Fernandez, and Harith Alani. 2017. “Statistical Semantic Classification of Crisis Information.”.
   Google Scholar
• Liu, Huawen, Shichao Zhang, and Xindong Wu. 2014. “MLSLR: Multilabel Learning Via Sparse Logistic Regression.” Information Sciences 281:310–320. https://doi.org/10.1016/j.ins.2014.05.013.
   Web of Science ®Google Scholar
• Marujo, Luis, Wang Ling, Isabel Trancoso, Chris Dyer, Alan W. Black, Anatole Gershman, David Martins de Matos, Joao P. Neto, and Jaime G. Carbonell. 2015. “Automatic Keyword Extraction on Twitter.” In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), 637–643. Cambridge, Massachusetts, United States: MIT Press.
   Google Scholar
• März, Luisa, Dietrich Trautmann, and Benjamin Roth. 2019. “Domain Adaptation for Part-of-Speech Tagging of Noisy User-generated Text.” arXiv, arXiv:1905.08920, preprint.
   Google Scholar
• Millstein, Frank. 2020. Natural Language Processing with Python: Natural Language Processing Using NLTK. Scotts Valley, California, USA: CreateSpace Independent Publishing Platform.
   Google Scholar
• Musaev, Aibek, De Wang, and Calton Pu. 2014. “LITMUS: A Multi-service Composition System for Landslide Detection.” IEEE Transactions on Services Computing 8 (5): 715–726. https://doi.org/10.1109/TSC.2014.2376558.
   Web of Science ®Google Scholar
• Nelakuditi, Kovida, Divya Sai Jitta, and Radhika Mamidi. 2018. “Part-of-Speech Tagging for Code Mixed English-Telugu Social Media Data.” In Computational Linguistics and Intelligent Text Processing: 17th International Conference, CICLing 2016, Konya, Turkey, April 3–9, 2016, Revised Selected Papers, Part I 17, 332–342. Springer.
   Google Scholar
• Ngamassi, Louis, Abish Malik, Jiawei Zhang, and David S. Ebert. 2017. “Social Media Visual Analytic Toolkits for Disaster Management: A Review of the Literature.” ISCRAM.
   Google Scholar
• Pezanowski, Scott, Alan M. MacEachren, Alexander Savelyev, and Anthony C. Robinson. 2018. “SensePlace3: A Geovisual Framework to Analyze Place–Time–Attribute Information in Social Media.” Cartography and Geographic Information Science 45 (5): 420–437. https://doi.org/10.1080/15230406.2017.1370391.
   Web of Science ®Google Scholar
• Prabhat, Anjuman, and Vikas Khullar. 2017. “Sentiment Classification on Big Data using Naïve Bayes and Logistic Regression.” In 2017 International Conference on Computer Communication and Informatics (ICCCI), 1–5. IEEE.
   Google Scholar
• Pranckevičius, Tomas, and Virginijus Marcinkevičius. 2016. “Application of Logistic Regression with Part-of-the-Speech Tagging for Multi-class Text Classification.” In 2016 IEEE 4th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE), 1–5. IEEE.
   Google Scholar
• Romero, Simone, and Karin Becker. 2019. “A Framework for Event Classification in Tweets Based on Hybrid Semantic Enrichment.” Expert Systems with Applications 118:522–538. https://doi.org/10.1016/j.eswa.2018.10.028.
   Web of Science ®Google Scholar
• Rossi, C., F. S. Acerbo, K. Ylinen, I. Juga, P. Nurmi, A. Bosca, F. Tarasconi, M. Cristoforetti, and A. Alikadic. 2018. “Early Detection and Information Extraction for Weather-induced Floods Using Social Media Streams.” International Journal of Disaster Risk Reduction 30:145–157. Communicating High Impact Weather: Improving Warnings and Decision Making Processes. https://www.sciencedirect.com/science/article/pii/S2212420918302735. https://doi.org/10.1016/j.ijdrr.2018.03.002.
   Web of Science ®Google Scholar
• Senaratne, Hansi, Arne Bröring, Tobias Schreck, and Dominic Lehle. 2014. “Moving on Twitter: Using Episodic Hotspot and Drift Analysis to Detect and Characterise Spatial Trajectories.” In Proceedings of the 7th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, 23–30. New York: ACM.
   Google Scholar
• Senaratne, Hansi, Dominic Lehle, and Tobias Schreck. 2022. “Characteristics Analysis of Moving Conversations to Detect Events on Twitter.” .” In 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 476–483. New York: IEEE Press.
   Google Scholar
• Senaratne, Hansi, Amin Mobasheri, Ahmed Loai Ali, Cristina Capineri, and Mordechai Haklay. 2017. “A Review of Volunteered Geographic Information Quality Assessment Methods.” International Journal of Geographical Information Science 31 (1): 139–167. https://doi.org/10.1080/13658816.2016.1189556.
   Web of Science ®Google Scholar
• Senaratne, Hansi, Martin Mühlbauer, Ralph Kiefl, Andrea Cárdenas, Lallu Prathapan, Torsten Riedlinger, Carolin Biewer, and Hannes Taubenböck. 2023. “The Unseen – An Investigative Analysis of Thematic and Spatial Coverage of News on the Ongoing Refugee Crisis in West Africa.” ISPRS International Journal of Geo-Information 12 (4): 175. https://doi.org/10.3390/ijgi12040175.
   Web of Science ®Google Scholar
• Shah, Kanish, Henil Patel, Devanshi Sanghvi, and Manan Shah. 2020. “A Comparative Analysis of Logistic Regression, Random Forest and KNN Models for the Text Classification.” Augmented Human Research 5 (1): 1–16. https://doi.org/10.1007/s41133-019-0017-2.
   Google Scholar
• Sloan, Luke, and Jeffrey Morgan. 2015. “Who Tweets with Their Location? Understanding the Relationship Between Demographic Characteristics and the Use of Geoservices and Geotagging on Twitter.” PLoS ONE 10 (11): e0142209. https://doi.org/10.1371/journal.pone.0142209.
   PubMed Web of Science ®Google Scholar
• Taubenböck, Hannes, Joachim Post, Achim Roth, Kai Zosseder, Günter Strunz, and Stefan Dech. 2008. “A Conceptual Vulnerability and Risk Framework As Outline to Identify Capabilities of Remote Sensing.” Natural Hazards and Earth System Sciences 8 (3): 409–420. https://doi.org/10.5194/nhess-8-409-2008.
   Web of Science ®Google Scholar
• Thomson, Robert, Christopher Dancy, Ayaz Hyder, and Halil Bisgin. 2018. Social, Cultural, and Behavioral Modeling: 11th International Conference, SBP-BRiMS 2018, Proceedings, Washington, DC, USA, July 10–13, 2018. Vol. 10899. Springer.
   Google Scholar
• UNDRR. 2017. “Sendai Framework for Disaster Risk Reduction 2015–2030.” Accessed May 24, 2023. https://www.undrr.org/publication/sendai-framework-disaster-risk-reduction-2015-2030
   Google Scholar
• Yen, Show-Jane, Yue-Shi Lee, Jia-Ching Ying, and Yu-Chieh Wu. 2011. “A Logistic Regression-based Smoothing Method for Chinese Text Categorization.” Expert Systems with Applications 38 (9): 11581–11590. https://doi.org/10.1016/j.eswa.2011.03.036.
   Web of Science ®Google Scholar
• Yu, Yuhai, Hongfei Lin, Jiana Meng, and Zhehuan Zhao. 2016. “Visual and Textual Sentiment Analysis of a Microblog Using Deep Convolutional Neural Networks.” Algorithms 9 (2): 41. https://doi.org/10.3390/a9020041.
   Web of Science ®Google Scholar
• Zhang, Boliang, Ying Lin, Xiaoman Pan, Di Lu, Jonathan May, Kevin Knight, and Heng Ji. 2018. “ELISA-EDL: A Cross-lingual Entity Extraction, Linking and Localization System.” In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, New Orleans, Louisiana, June 41–45. Association for Computational Linguistics. https://aclanthology.org/N18-5009
   Google Scholar