Muhammad Imran
Carlos Castillo
Fernando Diaz
ABSTRACT
Millions of people use social media to share information during disasters and mass emergencies. Information available on social media, particularly in the early hours of an event when few other sources are available, can be extremely valuable for emergency responders and decision makers, helping them gain situational awareness and plan relief efforts. Processing social media content to obtain such information involves solving multiple challenges, including parsing brief and informal messages, handling information overload, and prioritizing different types of information. These challenges can be mapped to information processing operations such as filtering, classifying, ranking, aggregating, extracting, and summarizing. This work highlights these challenges and presents state of the art computational techniques to deal with social media messages, focusing on their application to crisis scenarios.
- Mohammed Ali Al-garadi, Muhammad Sadiq Khan, Kasturi Dewi Varathan, Ghulam Mujtaba, and Abdelkodose M Al-Kabsi. 2016. Using online social networks to track a pandemic: A systematic review. Journal of biomedical informatics Vol. 62 (2016), 1--11. Google Scholar
Digital Library
- Firoj Alam, Muhammad Imran, and Ferda Ofli. 2017. Image4Act: Online Social Media Image Processing for Disaster Response. Proc. of ASONAM. 1--4. Google ScholarDigital Library
- James Allan. 2012. Topic detection and tracking: event-based information organization. Vol. Vol. 12. Springer Science & Business Media. Google ScholarDigital Library
- Javed Aslam, Fernando Diaz, Matthew Ekstrand-Abueg, Richard McCreadie, Virgil Pavlu, and Tetsuya Sakai. 2015. TREC 2014 temporal summarization track overview. Technical Report. NIST.Google Scholar
- Marco Avvenuti, Stefano Cresci, Andrea Marchetti, Carlo Meletti, and Maurizio Tesconi. 2014. EARS (earthquake alert and report system): a real time decision support system for earthquake crisis management. In Proc. of KDD. ACM, 1749--1758. Google ScholarDigital Library
- Michele Berlingerio, Francesco Calabrese, Giusy Di Lorenzo, Xiaowen Dong, Yiannis Gkoufas, and Dimitrios Mavroeidis. 2013. SaferCity: a system for detecting and analyzing incidents from social media Proc. of ICDM Workshops. IEEE, 1077--1080. Google ScholarDigital Library
- Jingwen Bian, Yang Yang, and Tat-Seng Chua. 2013. Multimedia summarization for trending topics in microblogs Proc. of CIKM. ACM, 1807--1812. Google ScholarDigital Library
- Carlos Castillo. 2016. Big crisis data: social media in disasters and time-critical situations. Cambridge University Press. Google Scholar
- Carlos Castillo, Marcelo Mendoza, and Barbara Poblete. 2011. Information credibility on twitter. In Proc. of WWW. ACM, 675--684. Google ScholarDigital Library
- Tao Chen, Dongyuan Lu, Min-Yen Kan, and Peng Cui. 2013. Understanding and classifying image tweets. In Proc. of ACM MM. ACM, 781--784. Google ScholarDigital Library
- Soudip Roy Chowdhury, Muhammad Imran, Muhammad Rizwan Asghar, Sihem Amer-Yahia, and Carlos Castillo. 2013. Tweet4act: Using incident-specific profiles for classifying crisis-related messages. Proc. of ISCRAM.Google Scholar
- Courtney D Corley, Chase Dowling, Stuart J Rose, and Taylor McKenzie. 2013. Social sensor analytics: Measuring phenomenology at scale Proc. of ISI. IEEE, 61--66.Google Scholar
- John Harrald and Theresa Jefferson. 2007. Shared situational awareness in emergency management mitigation and response Proc. of HICSS. IEEE, 23--23. Google ScholarDigital Library
- Amanda L Hughes and Leysia Palen. 2012. The evolving role of the public information officer: An examination of social media in emergency management. J. of Homeland Security and Emergency Management, Vol. 9, 1 (2012).Google ScholarCross Ref
- Amanda L Hughes, Steve Peterson, and Leysia Palen. 2014 a. Social media in emergency management. Issues in Disaster Science and Management: A Critical Dialogue Between Scientists and Emergency Managers (2014).Google Scholar
- Amanda L Hughes, Lise AA St Denis, Leysia Palen, and Kenneth M Anderson. 2014 b. Online public communications by police & fire services during the 2012 Hurricane Sandy Proc. of SIGCHI. ACM, 1505--1514. Google ScholarDigital Library
- Muhammad Imran and Carlos Castillo. 2015. Towards a data-driven approach to identify crisis-related topics in social media streams Proc. of WWW. ACM, 1205--1210. Google ScholarDigital Library
- Muhammad Imran, Carlos Castillo, Fernando Diaz, and Sarah Vieweg. 2015. Processing social media messages in mass emergency: A survey. ACM Computing Surveys (CSUR) Vol. 47, 4 (2015), 67. Google ScholarDigital Library
- Muhammad Imran, Carlos Castillo, Ji Lucas, Patrick Meier, and Sarah Vieweg. 2014. AIDR: Artificial intelligence for disaster response Proc. of WWW. ACM, 159--162. Google ScholarDigital Library
- Muhammad Imran, Sanjay Chawla, and Carlos Castillo. 2016 a. A robust framework for classifying evolving document streams in an expert-machine-crowd setting. In Proc. of ICDM. IEEE, 961--966.Google ScholarCross Ref
- Muhammad Imran, Prasenjit Mitra, and Carlos Castillo. 2016 b. Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messages Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016) (23--28). European Language Resources Association (ELRA), Paris, France.Google Scholar
- Muhammad Imran, Prasenjit Mitra, and Jaideep Srivastava. 2016 c. Enabling Rapid Classification of Social Media Communications During Crises. Int. J. of Inf. Sys. for Crisis Response and Management, Vol. 8, 3 (2016), 1--17. Google ScholarDigital Library
- Chris Kedzie, Kathleen McKeown, and Fernando Diaz. 2014. Summarizing disasters over time. In Proc. of KDD Workshops.Google Scholar
- Chris Kedzie, Kathleen McKeown, and Fernando Diaz. 2015. Predicting Salient Updates for Disaster Summarization. Proc. of ACL.Google ScholarCross Ref
- Yuan Liang, James Caverlee, and John Mander. 2013. Text vs. images: on the viability of social media to assess earthquake damage Proc. of WWW. ACM, 1003--1006. Google ScholarDigital Library
- Alan M MacEachren, Anuj Jaiswal, Anthony C Robinson, Scott Pezanowski, Alexander Savelyev, Prasenjit Mitra, Xiao Zhang, and Justine Blanford. 2011. Senseplace2: Geotwitter analytics support for situational awareness Proc. of VAST. IEEE, 181--190.Google Scholar
- Patrick Meier. 2015. Digital humanitarians: how big data is changing the face of humanitarian response. CRC Press. Google ScholarDigital Library
- Leonardo Neumeyer, Bruce Robbins, Anish Nair, and Anand Kesari. 2010. S4: Distributed stream computing platform. In Proc. of ICDM Workshops. IEEE, 170--177. Google ScholarDigital Library
- Dat Tien Nguyen, Kamla Al-Mannai, Shafiq R Joty, Hassan Sajjad, Muhammad Imran, and Prasenjit Mitra. 2017 a. Robust Classification of Crisis-Related Data on Social Networks Using Convolutional Neural Networks. In Proc. of ICWSM. 632--635.Google Scholar
- Dat Tien Nguyen, Firoj Alam, Ferda Ofli, and Muhammad Imran. 2017 b. Automatic Image Filtering on Social Networks Using Deep Learning and Perceptual Hashing During Crises. In Proc. of ISCRAM.Google Scholar
- Dat Tien Nguyen, Shafiq Joty, Muhammad Imran, Hassan Sajjad, and Prasenjit Mitra. 2016 a. Applications of Online Deep Learning for Crisis Response Using Social Media Information. arXiv preprint arXiv:1610.01030 (2016).Google Scholar
- Dat Tien Nguyen, Kamela Ali Al Mannai, Shafiq Joty, Hassan Sajjad, Muhammad Imran, and Prasenjit Mitra. 2016 b. Rapid Classification of Crisis-Related Data on Social Networks using Convolutional Neural Networks. arXiv preprint arXiv:1608.03902 (2016).Google Scholar
- Dat Tien Nguyen, Ferda Ofli, Muhammad Imran, and Prasenjit Mitra. 2017 c. Damage Assessment from Social Media Imagery Data During Disasters Proc. of ASONAM. 1--8.Google Scholar
- Ferda Ofli, Patrick Meier, Muhammad Imran, Carlos Castillo, Devis Tuia, Nicolas Rey, Julien Briant, Pauline Millet, Friedrich Reinhard, Matthew Parkan, et almbox. 2016. Combining human computing and machine learning to make sense of big (aerial) data for disaster response. Big data, Vol. 4, 1 (2016), 47--59.Google Scholar
- Alexandra Olteanu, Carlos Castillo, Fernando Diaz, and Sarah Vieweg. 2014. CrisisLex: A Lexicon for Collecting and Filtering Microblogged Communications in Crises. Proc. of ICWSM.Google Scholar
- Robin Peters and Porto de Albuqerque Joao. 2015. Investigating images as indicators for relevant social media messages in disaster management Proc. of ISCRAM.Google Scholar
- Robert Power, Bella Robinson, John Colton, and Mark Cameron. 2014. Emergency situation awareness: Twitter case studies Proc. of ISCRAM MED. Springer, 218--231.Google Scholar
- Hemant Purohit and Amit P Sheth. 2013. Twitris v3: From Citizen Sensing to Analysis, Coordination and Action. Proc. of ICWSM.Google Scholar
- Vahed Qazvinian, Emily Rosengren, Dragomir R Radev, and Qiaozhu Mei. 2011. Rumor has it: Identifying misinformation in microblogs Proc. of EMNLP. Association for Computational Linguistics, 1589--1599. Google ScholarDigital Library
- Alan Ritter, Oren Etzioni, Sam Clark, et almbox. 2012. Open domain event extraction from twitter. In Proc. of KDD. ACM, 1104--1112. Google ScholarDigital Library
- Bella Robinson, Robert Power, and Mark Cameron. 2013. A sensitive twitter earthquake detector. In Proc. of WWW. ACM, 999--1002. Google ScholarDigital Library
- Jakob Rogstadius, Maja Vukovic, CA Teixeira, Vassilis Kostakos, Evangelos Karapanos, and Jim Alain Laredo. 2013. CrisisTracker: Crowdsourced social media curation for disaster awareness. IBM J. of Research and Development Vol. 57, 5 (2013), 4--1. Google ScholarDigital Library
- Koustav Rudra, Siddhartha Banerjee, Niloy Ganguly, Pawan Goyal, Muhammad Imran, and Prasenjit Mitra. 2016. Summarizing Situational and Topical Information During Crises. arXiv preprint arXiv:1610.01561 (2016).Google Scholar
- Koustav Rudra, Ashish Sharma, Niloy Ganguly, and Muhammad Imran. 2017. Classifying Information from Microblogs during Epidemics Proceedings of the 2017 International Conference on Digital Health. ACM, 104--108. Google ScholarDigital Library
- Takeshi Sakaki, Makoto Okazaki, and Yutaka Matsuo. 2010. Earthquake shakes Twitter users: real-time event detection by social sensors Proc. of WWW. ACM, 851--860. Google ScholarDigital Library
- Diane H Sonnenwald and Linda G Pierce. 2000. Information behavior in dynamic group work contexts: interwoven situational awareness, dense social networks and contested collaboration in command and control. Inf. Proc. & Mgmt., Vol. 36, 3 (2000), 461--479. Google ScholarDigital Library
- Kate Starbird, Leysia Palen, Amanda L Hughes, and Sarah Vieweg. 2010. Chatter on the red: what hazards threat reveals about the social life of microblogged information. In Proc. of CSCW. ACM, 241--250. Google ScholarDigital Library
- Sarah Vieweg, Carlos Castillo, and Muhammad Imran. 2014. Integrating social media communications into the rapid assessment of sudden onset disasters Proc. of SOCINFO. Springer, 444--461.Google Scholar
- Sarah Vieweg, Amanda L Hughes, Kate Starbird, and Leysia Palen. 2010. Microblogging during two natural hazards events: what twitter may contribute to situational awareness. In Proc. of SIGCHI. ACM, 1079--1088. Google ScholarDigital Library
- Jianshu Weng and Bu-Sung Lee. 2011. Event detection in twitter. Proc. of ICWSM Vol. 11 (2011), 401--408.Google Scholar
- Shize Xu, Liang Kong, and Yan Zhang. 2012. A picture paints a thousand words: a method of generating image-text timelines Proc. of CIKM. ACM, 2511--2514. Google ScholarDigital Library
Index Terms
- Processing Social Media Messages in Mass Emergency: Survey Summary
Recommendations
Processing Social Media Messages in Mass Emergency: A Survey
Social media platforms provide active communication channels during mass convergence and emergency events such as disasters caused by natural hazards. As a result, first responders, decision makers, and the public can use this information to gain ...
Social network analysis
Explores connections and patterns created by the aggregated interactions in Facebook pages during disaster responses.Analyzes social media data from the Facebook page of city of Baton Rouge during the 2016 Louisiana flood (Aug 12Dec 1, 2016).Analyzes ...
Exploitation of Social Media for Emergency Relief and Preparedness: Recent Research and Trends
Online Social Media, such as Twitter, Facebook and WhatsApp, are important sources of real-time information related to emergency events, including both natural calamities, man-made disasters, epidemics, and so on. There has been lot of recent work on ...
Comments