Processing Social Media Messages in Mass Emergency: A SurveyMuhammad Imran
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.
The Role of Social Media and Artificial Intelligence for Disaster ResponseMuhammad Imran
Keynote slides for ISCRAM 2016.
"Social Media platforms such as Twitter are invaluable sources of time-critical information. Information on social media communicated during emergencies convey timely and actionable information. For rapid crisis response, real-time insights are important for emergency responders. Although, many humanitarian organizations would like to use this information, however they struggle due a number of issues such as information overload, information vagueness, less credible and misinformation. In this talk, I will describe the role of social media and potential artificial intelligence computational techniques useful for humanitarian organizations and decision makers to make sense of social media data for rapid crisis response."
Introduction to Machine Learning: An Application to Disaster ResponseMuhammad Imran
Introduction to Machine Learning talk (part-2) focused on the applications of machine learning in the disaster response domain. In the first part of the talk, we presented different machine learning approaches.
Given the growth of social media and rapid evolution of Web of Data, we have unprecedented opportunities to improve crisis response by extracting social signals, creating spatio-temporal mappings, performing analytics on social and Web of Data, and supporting a variety of applications. Such applications can help provide situational awareness during an emergency, improve preparedness, and assist during the rebuilding/recovery phase of a disaster. Data mining can provide valuable insights to support emergency responders and other stakeholders during crisis. However, there are a number of challenges and existing computing technology may not work in all cases. Therefore, our objective here is to present the characterization of such data mining tasks, and challenges that need further research attention for leveraging social media and Web of Data to assist crisis response coordination.
Invited talk presented by Hemant Purohit (http://knoesis.org/researchers/hemant) at the NCSU workshop on IT for sustainable tourism development. The talk presents application of technology developed for crisis coordination into more general marketplace coordination via social media for helping suppliers (micro-entrepreneurs) and demanders (tourists).
Social Media & Web Mining for Public Services of Smart Cities - SSA TalkHemant Purohit
This talk at Data Science Seminar of SSA presents challenges and methods to model behavior on social media & Web for application opportunities for public services. The talk also demonstrates an in-depth case study of mining intentional behavior from the noisy natural language text of social media messages during disasters and how it could assist emergency services of future smart cities.
Public Health Crisis Analytics for Gender ViolenceHemant Purohit
The document discusses using social media data to analyze gender-based violence campaigns and public attitudes. It summarizes a study of cross-campaign participation on Twitter around three hashtags. Most users and tweets were individual rather than organizational. Few male users were observed. The document also describes a system called CitizenHelper for visualizing attitude trend analytics over time from social media to evaluate campaign effects and inform intervention events.
Processing Social Media Messages in Mass Emergency: A SurveyMuhammad Imran
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.
The Role of Social Media and Artificial Intelligence for Disaster ResponseMuhammad Imran
Keynote slides for ISCRAM 2016.
"Social Media platforms such as Twitter are invaluable sources of time-critical information. Information on social media communicated during emergencies convey timely and actionable information. For rapid crisis response, real-time insights are important for emergency responders. Although, many humanitarian organizations would like to use this information, however they struggle due a number of issues such as information overload, information vagueness, less credible and misinformation. In this talk, I will describe the role of social media and potential artificial intelligence computational techniques useful for humanitarian organizations and decision makers to make sense of social media data for rapid crisis response."
Introduction to Machine Learning: An Application to Disaster ResponseMuhammad Imran
Introduction to Machine Learning talk (part-2) focused on the applications of machine learning in the disaster response domain. In the first part of the talk, we presented different machine learning approaches.
Given the growth of social media and rapid evolution of Web of Data, we have unprecedented opportunities to improve crisis response by extracting social signals, creating spatio-temporal mappings, performing analytics on social and Web of Data, and supporting a variety of applications. Such applications can help provide situational awareness during an emergency, improve preparedness, and assist during the rebuilding/recovery phase of a disaster. Data mining can provide valuable insights to support emergency responders and other stakeholders during crisis. However, there are a number of challenges and existing computing technology may not work in all cases. Therefore, our objective here is to present the characterization of such data mining tasks, and challenges that need further research attention for leveraging social media and Web of Data to assist crisis response coordination.
Invited talk presented by Hemant Purohit (http://knoesis.org/researchers/hemant) at the NCSU workshop on IT for sustainable tourism development. The talk presents application of technology developed for crisis coordination into more general marketplace coordination via social media for helping suppliers (micro-entrepreneurs) and demanders (tourists).
Social Media & Web Mining for Public Services of Smart Cities - SSA TalkHemant Purohit
This talk at Data Science Seminar of SSA presents challenges and methods to model behavior on social media & Web for application opportunities for public services. The talk also demonstrates an in-depth case study of mining intentional behavior from the noisy natural language text of social media messages during disasters and how it could assist emergency services of future smart cities.
Public Health Crisis Analytics for Gender ViolenceHemant Purohit
The document discusses using social media data to analyze gender-based violence campaigns and public attitudes. It summarizes a study of cross-campaign participation on Twitter around three hashtags. Most users and tweets were individual rather than organizational. Few male users were observed. The document also describes a system called CitizenHelper for visualizing attitude trend analytics over time from social media to evaluate campaign effects and inform intervention events.
Ignite talk at ICCM-2013 at United Nations (UN) Nairobi by NSF SoCS project researcher, Hemant Purohit - 'How to Leverage Social Media Communities for Crisis Response Coordination' using Human+Machine computing
Key-message: We need to extract smart actionable data out of big crisis data to assist response coordination, by focusing on demand-supply centric technology.
More at Kno.e.sis' SOCS project page: http://knoesis.org/research/semsoc/projects/socs
Also, Crisis Informatics at Kno.e.sis: http://j.mp/CrisisRes
ICT for Disaster Risk Management-Managing Disaster Information-Global Risk Id...Global Risk Forum GRFDavos
The document discusses managing disaster information to support disaster risk reduction efforts. It outlines how establishing national disaster observatories can systematically collect, analyze, and disseminate disaster data to various stakeholders. This information can then be used to inform national disaster risk reduction strategies, risk assessments, and development decisions by providing evidence of hazards, vulnerabilities, and impacts. The document advocates for integrating disaster data into policy and planning to promote more effective disaster risk management.
Presentation at the Tow Center for Digital Journalism, Columbia University. November 14th, 2013.
VIDEO: http://new.livestream.com/accounts/1079539/events/2542929
http://towcenter.org/events/conversation-with-carlos-castillo/
1. The document discusses a study that mapped the information needs of decision makers during flood response in Bangladesh to available data sets, in order to identify information gaps. Interviews and focus groups identified timely and location-based information as the most important need not well covered.
2. The study recommends identifying information requirements and available data sources during preparedness to help address gaps in initial response. Future research aims to close gaps by linking disparate data sets and collecting community-level data with mobile apps.
3. The study was conducted in partnership with organizations implementing early warning systems on riverine islands in Bangladesh, to better support communities before, during and after floods.
Automatically Rank Social Media Requests for Emergency Services using Service...Hemant Purohit
Public expects a prompt response from online services, including emergency response organizations to requests for help posted on social media. However, the information overload experienced by these organizations, coupled with their limited human resources, challenges them to timely identifying and prioritizing such requests. We present a novel model to formally characterize social media requests and then, develop a Learning-to-Rank system using this model.
Paper: Purohit, H., Castillo, C., Imran, M., and Pandey, R. (2018). Social-EOC: Serviceability Model To Rank Social Media Requests for Emergency Operation Centers. ASONAM 2018.
Kno.e.sis Approach to Impactful Research, Creating Exceptional Careers & Economic Development outlines Amit Sheth's approach as the Executive Director of Kno.e.sis. It highlights the success of Kno.e.sis in graduating exceptional students who go on to have successful careers in academia, industry, and as entrepreneurs. It also summarizes Kno.e.sis' impactful research which has led to economic development and commercialization through startups like Cognovi Labs. The presentation concludes by outlining Kno.e.sis' funded projects totaling over $13 million from sources like NSF, NIH, DoD, and industry partners.
The case for integrating crisis response with social media American Red Cross
Social media has changed expectations around crisis response by allowing people to directly request help online. This has created challenges for emergency responders to monitor and respond to these requests in a timely manner. In response, volunteer groups have formed using technologies like Ushahidi to aggregate crisis information from social media and map it to help coordinate response efforts. Events like Crisis Camp and Random Hacks of Kindness bring technologists together to develop open-source tools to help address humanitarian crises. The Haiti earthquake saw many of these collaborative efforts unite to rapidly develop applications and share information to assist response and relief operations.
Twitris in Action - a review of its many applications Amit Sheth
Twitris is a technology developed at Kno.e.sis that provides real-time, actionable insights from social media data. It analyzes data through approaches like Sentiment-Emotion-Intent, Spatio-Temporal-Thematic, and People-Content-Network. Twitris has been applied in domains like disaster response, elections, public health, and social movements. It has been used to help coordinate responses during crises like hurricanes, floods, and tornadoes.
Slideshare lost the previous upload which had nearly 70K views. Re-uploading. http://knoesis.org/?q=node/2633
With the explosion in social media (1B+ Facebook users, 500M+ Twitter users) and ubiquitous mobile access (6B+ mobile phone subscribers) sharing their observations and opinions, we have unprecedented opportunities to extract social signals, create spatio-temporal mappings, perform analytics on social data, and support applications that vary from situational awareness during crisis response, preparedness and rebuilding phases to advanced analytics on social data, and gaining valuable insights to support improved decision making.This tutorial weaves three themes and corresponding relevant topics- a.) citizen sensing and crisis mapping, b.) technical challenges and recent research for leveraging citizen sensing to improve crisis response coordination, and c.) experiences in building robust and scalable platforms/systems. It will couple technical insights with identification of computational techniques and algorithms along with real-world examples. We will also do exemplary demos of the features in the Sahana, CrowdMap (Ushahidi's version) and Twitris platforms while elaborating on the practical issues and pitfalls of the development and operation of these large-scale platforms, especially during the real-time crisis response
Leveraging A Wiki To Enhance Virtual Collaboration In The Emergency DomainConnie White
In a crisis situation, critical success factors include good preparedness, the availability of
trustworthy information and reliable people, and the responders' ability to improvise with the available, functioning tools. Wikis can be used as collaborative group support systems to support these activities, especially for communities of practice that must operate as high reliability organizations. The advantages of using a wiki are especially beneficial in volatile environments, such as those in the emergency domain, where critical real-time decision making is required. An international wiki - emergenciWiki.org - has been created and is being used by both practitioners and academics. The conclusions include that wiki features and functionality, which are important for safetycritical work, should add a minimum of bureaucratic overhead while helping to establish trust and a sense of purpose and community among the users, strengthening each individual user's accountability for their actions, or easing the evaluation of information reliability. (*note emergenciWiki.org project is over)
Humanitarian Diplomacy in the Digital Age: Analysis and use of digital inform...Keith Powell
The document analyzes how information and communication technologies (ICT), specifically Ushahidi and Mission 4636, were used to gather and disseminate information during the 2010 Haitian earthquake. Ushahidi created an interactive crisis map using crowdsourced data from social media, SMS, and other sources. Mission 4636 set up an SMS shortcode for Haitians to communicate their needs. However, issues with the information included inaccurate geolocations from untrained volunteers and limited use by responders unfamiliar with the tools. Overall, while ICT played a role, its impact appears exaggerated, as there was little evidence information was used substantially for humanitarian diplomacy.
This document discusses India's use of information and communication technologies (ICT) in disaster management. It outlines NDMA's vision of building a disaster resilient India through prevention, mitigation, preparedness and efficient response. It then describes India's Disaster Management Information System which uses ICT like call centers, websites and data centers to collect and share data before, during and after disasters to aid vulnerability analysis, risk assessment, preparedness and post-disaster recovery. Various ICT tools are also discussed that can help with early warning, forecasting, detection of chemical, biological and radiological agents, and coordination between different agencies for efficient disaster response.
The document is the World Disasters Report 2013, which focuses on technology and the future of humanitarian action. It explores how information and communication technologies can help humanitarian organizations, governments, and communities prepare for and respond to disasters. The report examines how technologies can help put communities at the center of humanitarian response. It also considers the challenges of technologies, such as reducing direct interaction between aid workers and communities. The report argues for more systematic evaluation of how technologies contribute to humanitarian action.
International Day for Disaster Reduction at the World Bank
Disaster Risk Management in the Information Age
A joint training workshop by GICT, GFDRR, infoDev and LCSUW to mark the International Day for Disaster Reduction
Statement for the Record of Heather Blanchard, Co Founder of CrisisCommons before the Ad Hoc Subcommittee on Disaster Recovery and Intergovernmental Affairs, Homeland Security and Governmental Affairs Committee, United States Senate on May 19, 2011
1) The document discusses how participatory culture, open data, and technology can help expand crisis management capacity.
2) It provides examples of how volunteers and public participation helped map needs and resources for crisis response through initiatives like CrisisCamp Haiti.
3) Key recommendations are to include participatory communities in crisis response planning, create missions to coordinate volunteer efforts, invest in open data preparedness, and engage communities outside of traditional organizational boundaries.
The Digital Humanitarian Moment: New Practices, Knowledge Politics, and Phila...Ryan Burns
Digital humanitarianism alters how data is collected and represented in humanitarian responses. It emerges at the intersection of new mapping technologies, practices, and philanthropy-capitalism. Specifically:
1. Social media allows needs to be crowdsourced, but these needs must be "tamed" and filtered for operational use.
2. Needs are represented to construct "needy subjects" through place-based and temporal framings to justify interventions.
3. It enables further private sector involvement through philanthropy-capitalism, which depoliticizes humanitarianism and naturalizes tradeoffs.
Digital humanitarianism is shaping the humanitarian sector and broader political and economic relationships through knowledge politics around data collection and
Presentation to National Academy of Science workshop on Public Response to Alerts and Warnings Using Social Media. I argued that the citizen science model, in which volunteers contribute to substantive scientific research, is a great model for how to involve the general public in making accurate, actionable social media posts (Twitter, Twitvid, Facebook) that first responders can use to direct their efforts in a disaster.
Transforming Social Big Data into Timely Decisions and Actions for Crisis Mi...Amit Sheth
Keynote @ Exploitation of Social Media for Emergency Relief and Preparedness (SMERP)
Co-located with: The Web Conference 2018 (formerly WWW)
Lyon, France. 23 April 2018
Abstract:
Crises are imposing massive costs to economies worldwide. Natural disasters caused record $306 billion in damage to the U.S. in 2017! Real-time gathering of relevant data through ubiquitous presence of mobile technologies and the ability to disseminate them through social media has forever changed how disaster and health crisis monitoring and response are now carried out. Both tradition crisis response organization as well as temporary, informal, self-organized and community-based organizations have come to increasingly rely on social media. Furthermore, ability to collect, repurpose and reuse data from past events is helping with preparedness and planning for future events.
In this talk, I will review our extensive experience on (a) interactions with variety of stakeholders involved in emergency response at city, county, country and international levels, (b) research on real-time social media analysis spanning spatio-temporal-thematic; people-content-network; linguistic-sentiment-emotion-intent analysis dimensions, (c) development and use of crisis response specific tools (location identification, demand-supply match) and the comprehensive Twitris semantic social intelligence system (which is also commercialized as Cognovi Labs), and (d) a variety of real-world evaluations and real-time uses (e.g., supplying data for Google Crisis map during Uttarakhand Floods, rescue during Kashmir Floods, neighborhood image map during Chennai Floods, providing information to FEMA during Oklahoma tornados), spread of disease and epidemiology (e.g., Zika spread), metro-level multi-agency disaster preparedness exercise, etc.
https://www.cse.iitk.ac.in/users/kripa/smerp2018/SMERP-at-Web2018-keynote.pdf
Emergency Management in the age of social convergencePatrice Cloutier
Conference on social media use in emergency management given at the Social Media in Government Conference on Oct. 3, 2011 for the Conference Board of Canada.
Ignite talk at ICCM-2013 at United Nations (UN) Nairobi by NSF SoCS project researcher, Hemant Purohit - 'How to Leverage Social Media Communities for Crisis Response Coordination' using Human+Machine computing
Key-message: We need to extract smart actionable data out of big crisis data to assist response coordination, by focusing on demand-supply centric technology.
More at Kno.e.sis' SOCS project page: http://knoesis.org/research/semsoc/projects/socs
Also, Crisis Informatics at Kno.e.sis: http://j.mp/CrisisRes
ICT for Disaster Risk Management-Managing Disaster Information-Global Risk Id...Global Risk Forum GRFDavos
The document discusses managing disaster information to support disaster risk reduction efforts. It outlines how establishing national disaster observatories can systematically collect, analyze, and disseminate disaster data to various stakeholders. This information can then be used to inform national disaster risk reduction strategies, risk assessments, and development decisions by providing evidence of hazards, vulnerabilities, and impacts. The document advocates for integrating disaster data into policy and planning to promote more effective disaster risk management.
Presentation at the Tow Center for Digital Journalism, Columbia University. November 14th, 2013.
VIDEO: http://new.livestream.com/accounts/1079539/events/2542929
http://towcenter.org/events/conversation-with-carlos-castillo/
1. The document discusses a study that mapped the information needs of decision makers during flood response in Bangladesh to available data sets, in order to identify information gaps. Interviews and focus groups identified timely and location-based information as the most important need not well covered.
2. The study recommends identifying information requirements and available data sources during preparedness to help address gaps in initial response. Future research aims to close gaps by linking disparate data sets and collecting community-level data with mobile apps.
3. The study was conducted in partnership with organizations implementing early warning systems on riverine islands in Bangladesh, to better support communities before, during and after floods.
Automatically Rank Social Media Requests for Emergency Services using Service...Hemant Purohit
Public expects a prompt response from online services, including emergency response organizations to requests for help posted on social media. However, the information overload experienced by these organizations, coupled with their limited human resources, challenges them to timely identifying and prioritizing such requests. We present a novel model to formally characterize social media requests and then, develop a Learning-to-Rank system using this model.
Paper: Purohit, H., Castillo, C., Imran, M., and Pandey, R. (2018). Social-EOC: Serviceability Model To Rank Social Media Requests for Emergency Operation Centers. ASONAM 2018.
Kno.e.sis Approach to Impactful Research, Creating Exceptional Careers & Economic Development outlines Amit Sheth's approach as the Executive Director of Kno.e.sis. It highlights the success of Kno.e.sis in graduating exceptional students who go on to have successful careers in academia, industry, and as entrepreneurs. It also summarizes Kno.e.sis' impactful research which has led to economic development and commercialization through startups like Cognovi Labs. The presentation concludes by outlining Kno.e.sis' funded projects totaling over $13 million from sources like NSF, NIH, DoD, and industry partners.
The case for integrating crisis response with social media American Red Cross
Social media has changed expectations around crisis response by allowing people to directly request help online. This has created challenges for emergency responders to monitor and respond to these requests in a timely manner. In response, volunteer groups have formed using technologies like Ushahidi to aggregate crisis information from social media and map it to help coordinate response efforts. Events like Crisis Camp and Random Hacks of Kindness bring technologists together to develop open-source tools to help address humanitarian crises. The Haiti earthquake saw many of these collaborative efforts unite to rapidly develop applications and share information to assist response and relief operations.
Twitris in Action - a review of its many applications Amit Sheth
Twitris is a technology developed at Kno.e.sis that provides real-time, actionable insights from social media data. It analyzes data through approaches like Sentiment-Emotion-Intent, Spatio-Temporal-Thematic, and People-Content-Network. Twitris has been applied in domains like disaster response, elections, public health, and social movements. It has been used to help coordinate responses during crises like hurricanes, floods, and tornadoes.
Slideshare lost the previous upload which had nearly 70K views. Re-uploading. http://knoesis.org/?q=node/2633
With the explosion in social media (1B+ Facebook users, 500M+ Twitter users) and ubiquitous mobile access (6B+ mobile phone subscribers) sharing their observations and opinions, we have unprecedented opportunities to extract social signals, create spatio-temporal mappings, perform analytics on social data, and support applications that vary from situational awareness during crisis response, preparedness and rebuilding phases to advanced analytics on social data, and gaining valuable insights to support improved decision making.This tutorial weaves three themes and corresponding relevant topics- a.) citizen sensing and crisis mapping, b.) technical challenges and recent research for leveraging citizen sensing to improve crisis response coordination, and c.) experiences in building robust and scalable platforms/systems. It will couple technical insights with identification of computational techniques and algorithms along with real-world examples. We will also do exemplary demos of the features in the Sahana, CrowdMap (Ushahidi's version) and Twitris platforms while elaborating on the practical issues and pitfalls of the development and operation of these large-scale platforms, especially during the real-time crisis response
Leveraging A Wiki To Enhance Virtual Collaboration In The Emergency DomainConnie White
In a crisis situation, critical success factors include good preparedness, the availability of
trustworthy information and reliable people, and the responders' ability to improvise with the available, functioning tools. Wikis can be used as collaborative group support systems to support these activities, especially for communities of practice that must operate as high reliability organizations. The advantages of using a wiki are especially beneficial in volatile environments, such as those in the emergency domain, where critical real-time decision making is required. An international wiki - emergenciWiki.org - has been created and is being used by both practitioners and academics. The conclusions include that wiki features and functionality, which are important for safetycritical work, should add a minimum of bureaucratic overhead while helping to establish trust and a sense of purpose and community among the users, strengthening each individual user's accountability for their actions, or easing the evaluation of information reliability. (*note emergenciWiki.org project is over)
Humanitarian Diplomacy in the Digital Age: Analysis and use of digital inform...Keith Powell
The document analyzes how information and communication technologies (ICT), specifically Ushahidi and Mission 4636, were used to gather and disseminate information during the 2010 Haitian earthquake. Ushahidi created an interactive crisis map using crowdsourced data from social media, SMS, and other sources. Mission 4636 set up an SMS shortcode for Haitians to communicate their needs. However, issues with the information included inaccurate geolocations from untrained volunteers and limited use by responders unfamiliar with the tools. Overall, while ICT played a role, its impact appears exaggerated, as there was little evidence information was used substantially for humanitarian diplomacy.
This document discusses India's use of information and communication technologies (ICT) in disaster management. It outlines NDMA's vision of building a disaster resilient India through prevention, mitigation, preparedness and efficient response. It then describes India's Disaster Management Information System which uses ICT like call centers, websites and data centers to collect and share data before, during and after disasters to aid vulnerability analysis, risk assessment, preparedness and post-disaster recovery. Various ICT tools are also discussed that can help with early warning, forecasting, detection of chemical, biological and radiological agents, and coordination between different agencies for efficient disaster response.
The document is the World Disasters Report 2013, which focuses on technology and the future of humanitarian action. It explores how information and communication technologies can help humanitarian organizations, governments, and communities prepare for and respond to disasters. The report examines how technologies can help put communities at the center of humanitarian response. It also considers the challenges of technologies, such as reducing direct interaction between aid workers and communities. The report argues for more systematic evaluation of how technologies contribute to humanitarian action.
International Day for Disaster Reduction at the World Bank
Disaster Risk Management in the Information Age
A joint training workshop by GICT, GFDRR, infoDev and LCSUW to mark the International Day for Disaster Reduction
Statement for the Record of Heather Blanchard, Co Founder of CrisisCommons before the Ad Hoc Subcommittee on Disaster Recovery and Intergovernmental Affairs, Homeland Security and Governmental Affairs Committee, United States Senate on May 19, 2011
1) The document discusses how participatory culture, open data, and technology can help expand crisis management capacity.
2) It provides examples of how volunteers and public participation helped map needs and resources for crisis response through initiatives like CrisisCamp Haiti.
3) Key recommendations are to include participatory communities in crisis response planning, create missions to coordinate volunteer efforts, invest in open data preparedness, and engage communities outside of traditional organizational boundaries.
The Digital Humanitarian Moment: New Practices, Knowledge Politics, and Phila...Ryan Burns
Digital humanitarianism alters how data is collected and represented in humanitarian responses. It emerges at the intersection of new mapping technologies, practices, and philanthropy-capitalism. Specifically:
1. Social media allows needs to be crowdsourced, but these needs must be "tamed" and filtered for operational use.
2. Needs are represented to construct "needy subjects" through place-based and temporal framings to justify interventions.
3. It enables further private sector involvement through philanthropy-capitalism, which depoliticizes humanitarianism and naturalizes tradeoffs.
Digital humanitarianism is shaping the humanitarian sector and broader political and economic relationships through knowledge politics around data collection and
Presentation to National Academy of Science workshop on Public Response to Alerts and Warnings Using Social Media. I argued that the citizen science model, in which volunteers contribute to substantive scientific research, is a great model for how to involve the general public in making accurate, actionable social media posts (Twitter, Twitvid, Facebook) that first responders can use to direct their efforts in a disaster.
Transforming Social Big Data into Timely Decisions and Actions for Crisis Mi...Amit Sheth
Keynote @ Exploitation of Social Media for Emergency Relief and Preparedness (SMERP)
Co-located with: The Web Conference 2018 (formerly WWW)
Lyon, France. 23 April 2018
Abstract:
Crises are imposing massive costs to economies worldwide. Natural disasters caused record $306 billion in damage to the U.S. in 2017! Real-time gathering of relevant data through ubiquitous presence of mobile technologies and the ability to disseminate them through social media has forever changed how disaster and health crisis monitoring and response are now carried out. Both tradition crisis response organization as well as temporary, informal, self-organized and community-based organizations have come to increasingly rely on social media. Furthermore, ability to collect, repurpose and reuse data from past events is helping with preparedness and planning for future events.
In this talk, I will review our extensive experience on (a) interactions with variety of stakeholders involved in emergency response at city, county, country and international levels, (b) research on real-time social media analysis spanning spatio-temporal-thematic; people-content-network; linguistic-sentiment-emotion-intent analysis dimensions, (c) development and use of crisis response specific tools (location identification, demand-supply match) and the comprehensive Twitris semantic social intelligence system (which is also commercialized as Cognovi Labs), and (d) a variety of real-world evaluations and real-time uses (e.g., supplying data for Google Crisis map during Uttarakhand Floods, rescue during Kashmir Floods, neighborhood image map during Chennai Floods, providing information to FEMA during Oklahoma tornados), spread of disease and epidemiology (e.g., Zika spread), metro-level multi-agency disaster preparedness exercise, etc.
https://www.cse.iitk.ac.in/users/kripa/smerp2018/SMERP-at-Web2018-keynote.pdf
Emergency Management in the age of social convergencePatrice Cloutier
Conference on social media use in emergency management given at the Social Media in Government Conference on Oct. 3, 2011 for the Conference Board of Canada.
Humanitarian Informatics Approach for Cooperation between Citizens and Organi...Hemant Purohit
This document discusses using a humanitarian informatics approach to facilitate cooperation between citizens and organizational decision makers during crisis situations. It proposes mining and managing social data generated by citizens to address organizations' information needs and challenges of articulation and awareness. Specifically, it involves extracting, classifying, and modeling social data to provide actionable information aligned with organizations' process-driven needs for decision making during disasters and other humanitarian efforts. The approach aims to leverage citizens' massive social media data generation to help organizations that have more defined roles and information needs but less direct access to data.
Tools and processes in digital voluntarismperaarvik
Svend-Jonas Schelhorn at the seminar: Digital Humanitarianism and Networked Crisis Support, Bergen Academy of Art and Design, Bergen, Norway, 19th October 2013
Digital Humanitarians is a wide description of individuals and NGOs using digital tools for collaboration, mapping, analyzing or data-mining for humanitarian purposes and in humanitarian contexts. They typically engage for humanitarian crises, natural disasters, democracy projects, human rights monitoring or disaster preparedness. There are digital tools, procedures and ethical questions they all have in common.
1) The document discusses the roles and benefits of using social media for emergency management and natural disaster response.
2) Key benefits include improving situational awareness, supporting two-way communication, and expanding engagement with stakeholders.
3) Social media can be used effectively during all phases of disaster management including preparedness, response, and recovery for functions like information dissemination, alerts and warnings, assistance requests, and monitoring.
This document summarizes a presentation about using multimedia technologies for emergency situations. It discusses:
1) The potential of emerging multimedia technologies like smartphones and social media to help with disaster response and management by providing real-time situation reports and coordinating relief efforts.
2) Prototype applications that have been developed like one for the Thai floods that used flood level and shelter data along with tweets to help direct aid.
3) Remaining research challenges around issues like human reporting of data, real-time situation recognition from multiple data streams, and predictive analytics.
4) The vision of building a global "situation map" by analyzing the billions of photos uploaded from smartphones to help recognize situations worldwide.
En annexe de la présentation 'Technologie et humanitaire' faite aux déléguées internationaux de la Croix-Rouge française en 2012, voici une liste de liens & ressources de référence dans le domaine des NTIC appliquées à l'humanitaire, la préparation aux catastrophes, le développement: blogs de référence, sites portail, etc.
Téléchargez la présentation pour obtenir le document avec les liens cliquables (sur la page de commentaires)
Heather Blanchard, Co Founder of CrisisCommons, presentation at the Fleming Europe's 2nd Annual Geospatial Conference (http://www.flemingeurope.com/aviation-and-defence-conferences/europe/2nd-annual-geospatial-intelligence-summit)
1) The document discusses how social media and mobile technologies have empowered citizens and changed emergency response by allowing people to participate through sharing information.
2) It outlines that emergency managers must now respond to incidents, warn the public, monitor and analyze social media, and communicate in real-time across platforms.
3) Several case studies of disasters are presented where social media played a key role in coordination, mapping requests for assistance, and disseminating information when other channels were unavailable.
Web 2.0 Technology Building Situational Awareness: Free and Open Source Too...Connie White
covers ways to use web apps, smart phones and free disaster management software like Sahana Eden, which offer agencies free and open source tools to customize and build situational awareness for their own agency or organizational needs.
This document discusses the rise of social convergence and its impact on emergency management. It outlines how mobile technologies and social media now enable citizens to actively participate during emergencies by sharing information and participating in crowdsourcing. This empowered citizenry generates large amounts of user-generated data that emergency managers must now integrate into their response if they want to remain relevant. The document analyzes several recent disaster case studies and proposes a six-step approach for emergency managers to adopt social media into their operations.
This document summarizes a workshop on digital tools for monitoring and evaluation (M&E) and citizen engagement. The purpose of the workshop is to 1) survey the shift from one-way to two-way communication flows, 2) outline key crowdsourcing and data collection tools for NGOs, and 3) assess implications for citizen engagement and governance reform. The workshop then discusses how digital M&E is tapping into crowd-sourced data using mobile phones and tools like FrontlineSMS, Ushahidi, and social media. Examples from Kenya, Haiti, and political campaigns in the US and elsewhere demonstrate how crowdsourced data has supported disaster response and political organizing. The document concludes with framing how digital tools
Human-AI Collaborationfor Virtual Capacity in Emergency Operation Centers (E...Hemant Purohit
Describes different use-cases for how AI technologies can help Emergency Management agencies for building virtual capacity in monitoring online data for situational awareness, decision support, and public communication in EOCs during disaster events.
Talk by Dr. Hemant Purohit, Humanitarian Informatics Lab, George Mason University -- https://mason.gmu.edu/~hpurohit
Dave Harte- The Timely Information ProjectPaul Hadley
Digital Birmingham have been commissioned by the Department for Communities and Local Government (CLG) to develop pilot projects that empower citizens to use data and information to better contribute to local decision making. Dave Harte tells us about this, alongside a number of other projects to make Birmingham a 'digital city' by 2010.
Digital intermediation: Towards Transparent Public Automated MediaUniversity of Sydney
The document discusses digital intermediation, which refers to the combination of data (online content producers) and algorithms (automated decision making within media systems) and how they create new forms of online communities and knowledge exchange. It examines digital influencers and micro-platformization, where digital agencies ensure advertisers receive the appropriate influencer. It proposes three potential applications of digital intermediation: applying it to public service media, policy recommendations on regulatory systems, and designing algorithmic transparency interfaces. The overall aim is to understand how this new media ecosystem works and provide recommendations to help media organizations engage audiences on important issues.
Similar to Real-Time Processing of Social Media Content for Social Good (20)
Damage Assessment from Social Media Imagery Data During DisastersMuhammad Imran
Rapid access to situation-sensitive data through social media networks creates new opportunities to address a number of real-world problems. Damage assessment during dis- asters is a core situational awareness task for many humanitarian organizations that traditionally takes weeks and months. In this work, we analyze images posted on social media platforms during natural disasters to determine the level of damage caused by the disasters. We employ state-of-the-art machine learning techniques to perform an extensive experimentation of damage assessment using images from four major natural disasters. We show that the domain-specific fine-tuning of deep Convolutional Neural Networks (CNN) outperforms other state-of-the-art techniques such as Bag-of-Visual-Words (BoVW). High classification ac- curacy under both event-specific and cross-event test settings demonstrate that the proposed approach can effectively adapt deep-CNN features to identify the severity of destruction from social media images taken after a disaster strike.
Image4Act: Online Social Media Image Processing for Disaster ResponseMuhammad Imran
We present an end-to-end social media image processing system called Image4Act. The system aims at collecting, denoising, and classifying imagery content posted on social media platforms to help humanitarian organizations in gaining situational awareness and launching relief operations. The system combines human computation and machine learning techniques to process high-volume social media imagery content in real time during natural and human-made disasters. To cope with the noisy nature of the social media imagery data, we use a deep neural network and perceptual hashing techniques to filter out irrelevant and duplicate images. Furthermore, we present a specific use case to assess the severity of infrastructure damage incurred by a disaster. The evaluations of the system on existing disaster datasets as well as a real-world deployment during a recent cyclone prove the effectiveness of the system.
AIDR Tutorial (Artificial Intelligence for Disaster Response)Muhammad Imran
This document provides an overview of the AIDR (Artificial Intelligence for Disaster Response) system, including how it collects Twitter data through keywords, geographic regions, and following users. It also describes how AIDR allows users to classify collected data by defining classifiers and labels, and how the classifiers are generated based on human-tagged tweets.
A Robust Framework for Classifying Evolving Document Streams in an Expert-Mac...Muhammad Imran
An emerging challenge in the online classification of social media data streams is to keep the categories used for classification up-to-date. In this paper, we propose an innovative framework based on an Expert-Machine-Crowd (EMC) triad to help categorize items by continuously identifying novel concepts in heterogeneous data streams often riddled with outliers. We unify constrained clustering and outlier detection by formulating a novel optimization problem: COD-Means. We design an algorithm to solve the COD-Means problem and show that COD-Means will not only help detect novel categories but also seamlessly discover human annotation errors and improve the overall quality of the categorization process. Experiments on diverse real data sets demonstrate that our approach is both effective and efficient.
Summarizing Situational Tweets in Crisis ScenarioMuhammad Imran
During mass convergence events such as natural disasters, microblogging platforms like Twitter are widely used by affected people to post situational awareness messages. These crisis related messages disperse among multiple categories like infrastructure damage, information about missing, injured, and dead people etc. The challenge here is to extract important situational updates from these messages, assign them appropriate informational categories, and finally summarize big trove of information in each category. In this paper, we propose a novel framework which first assigns tweets into different situational classes and then summarize those tweets. In the summarization phase, we propose a two stage summarization framework which first extracts a set of important tweets from the whole set of information through an Integer-linear programming (ILP) based optimization technique and then follows a word graph and content word based abstractive summarization technique to produce the final summary. Our method is time and memory efficient and outperforms the baseline in terms of quality, coverage of events, locations et al., effectiveness, and utility in disaster scenarios.
Artificial Intelligence for Disaster ResponseMuhammad Imran
AIDR is a free open-source platform that uses machine learning and crowdsourcing to automatically filter and classify relevant tweets during humanitarian crises. It collects tweets based on keywords, hashtags, location, and followed users. Classifiers then tag tweets with categories like donations, damage reports, or eyewitness accounts. The platform achieves around 75% accuracy in classification by training models on tagged tweets and leveraging random forest algorithms.
A Real-time Heuristic-based Unsupervised Method for Name Disambiguation in Di...Muhammad Imran
This paper addresses the baffling problem of name disam- biguation in the context of digital libraries that administer bibliographic citations. The problem emanates when multi- ple authors share a common name or when multiple name variations of an author appear in citation records. Name dis- ambiguation is not trivial to solve, and most of the digital libraries do not provide an efficient way to accurately iden- tify the citation records of an author. Furthermore, lack of complete meta-data information in digital libraries hinders the existence of generic algorithm that can be applicable on any dataset. We propose a heuristic-based, unsupervised and adaptive method that also embraces users’ interaction to count users’ feedback in disambiguation process. Moreover, the method exploits important features associated with an author and citation records such as co-authors, affiliation, publication title, venue etc., and contrives a conspicuous multilayer hierarchical clustering algorithm, which tunes it- self according to the available information and form clusters of unambiguous records. Our experiments on a set of re- searchers that are contemplated to be highly ambiguous de- cisively produced high precision and recall results and affirm the viability of our algorithm.
Coordinating Human and Machine Intelligence to Classify Microblog Communica0o...Muhammad Imran
An emerging paradigm for the processing of data streams involves human and machine computation working together, allowing human intelligence to process large-scale data. We apply this approach to the classification of crisis-related messages in microblog streams. We begin by describing the platform AIDR (Artificial Intelligence for Disaster Response), which collects human annotations over time to create and maintain automatic supervised classifiers for social media messages. Next, we study two significant challenges in its design: (1) identifying which elements must be labeled by humans, and (2) determining when to ask for such annotations to be done. The first challenge is selecting the items to be labeled by crowdsourcing workers to maximize the productivity of their work. The second challenge is to schedule the work in order to reliably maintain high classification accuracy over time. We provide and validate answers to these challenges by extensive experimentation on real- world datasets.
Tweet4act: Using Incident-Specific Profiles for Classifying Crisis-Related Me...Muhammad Imran
This work describes our work presented at the ISCRAM-2013 conference. We presented Tweet4act system, which is used to detect and classify crisis-related messages communicated over a microblogging platform. Our system relies on extracting content features from each message. These features and the use of an incident-specific dictionary allow us to determine the period type of an incident that each message belongs to.
Extracting Information Nuggets from Disaster-Related Messages in Social MediaMuhammad Imran
This document discusses extracting useful information from social media messages during disasters. It outlines filtering disaster-related tweets, classifying them by type (e.g. caution/advice, casualties), and extracting key information within tweets (e.g. locations, needs). The approach is demonstrated on datasets from the 2011 Joplin tornado and 2012 Hurricane Sandy. Automatic classification achieves over 80% accuracy for some classes. Information extraction obtains up to 90% precision. Ongoing work includes providing these tools as a machine learning service to help during crises.
This document proposes domain-specific mashups that are tailored for specific application domains. It argues that generic mashup tools are difficult to design in a way that balances generality, expressiveness, and simplicity. The approach presented involves developing domain-specific mashup tools with domain concept models and mashup meta-models mapped to domain processes. This reduces generality but allows domain experts to develop mashups using domain terminology and processes. An architecture is presented involving shared memory and a mashup engine to execute components defined in domain-specific mashup models. Future work involves extending an existing mashup tool to support this domain-specific approach.
We are going to represent a Mashup platform for the research evaluation. This talk was given at 2nd Search computing workshop in Como, italy on 27-may-2010.
ResEval: Resource-oriented Research Impact Evaluation platformMuhammad Imran
This document proposes a new open and resource-oriented platform for research impact evaluation. It discusses problems with existing solutions like limited data sources and predefined metrics. The proposed solution features a common platform to access various scientific resources, support for personalized metrics, natural language queries, and evaluation of individuals and groups. The architecture defines three layers and prototypes have been implemented for individual/contribution evaluation and group comparison. Future work includes improving the language module and adding more prototype options.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Leonel Morgado
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...Sérgio Sacani
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...Scintica Instrumentation
Targeting Hsp90 and its pathogen Orthologs with Tethered Inhibitors as a Diagnostic and Therapeutic Strategy for cancer and infectious diseases with Dr. Timothy Haystead.
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
Immersive Learning That Works: Research Grounding and Paths ForwardLeonel Morgado
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
The cost of acquiring information by natural selectionCarl Bergstrom
This is a short talk that I gave at the Banff International Research Station workshop on Modeling and Theory in Population Biology. The idea is to try to understand how the burden of natural selection relates to the amount of information that selection puts into the genome.
It's based on the first part of this research paper:
The cost of information acquisition by natural selection
Ryan Seamus McGee, Olivia Kosterlitz, Artem Kaznatcheev, Benjamin Kerr, Carl T. Bergstrom
bioRxiv 2022.07.02.498577; doi: https://doi.org/10.1101/2022.07.02.498577
Authoring a personal GPT for your research and practice: How we created the Q...Leonel Morgado
Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.
ESR spectroscopy in liquid food and beverages.pptxPRIYANKA PATEL
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
2. Outline
• P1: Background of Humanitarian CompuBng (10%)
– Sudden-onset emergencies, Time-cri,cal situa,ons
– Social Good factors
– Aid and informa,on needs
• P2: The Role of Social Media for Social Good (20%)
– Par,cular focus on micro-blogging plaKorms
– Availability of various types of informa,on and opportuni,es
• P3: The Role of ArBficial Intelligence for Social Good (70%)
– How AI is useful in crisis response
– Various AI techniques, approaches, and tools
– Work of crisis compu,ng group at QCRI
– Ongoing research
– Future direc,ons
3. Aid Needs, InformaBon Needs, and Gaps
Info. Info. Info.
Disaster event (earthquake, flood) Urgent needs of affected people
InformaBon gathering
Humanitarian organizaBons and local administraBon
InformaBon gathering,
especially in real-Bme, is
the most challenging part
Relief operaBons
- Food, water
- Shelter
- Medical assistance
- DonaBons
- Service and uBliBes
4. Aid Needs, InformaBon Needs, and Gaps
Info. Info. Info.
Disaster event (earthquake, flood) Urgent needs of affected people
InformaBon gathering
Humanitarian organizaBons and local administraBon
InformaBon gathering,
especially in real-Bme, is
the most challenging part
Relief operaBons
- Food, water
- Shelter
- Medical assistance
- DonaBons
- Service and uBliBes
--Informa,on Bestows Power--
Will access to informaBon solve the problem?
66. IdenBficaBon of Novel Categories
Classes.
- Injured people
- Infrastructure damage
- Shelter needs
- Dona,on requests
- Missing or stranded people
- Different health issues
- Novel urgent needs like
- Blankets
- Medicine
- Schools shut
- Airport closed/open
- …
Pre-defined classes Unseen classes (Miscellaneous)
Keep in mind we have a new class
“Miscellaneous”
67. Expert-Machine-Crowd Sesng
Constraints Outlier DetecBon (COD-Means):
1. Constraints forma,on using classified items
2. Clustering using COD-Means
3. Labeling errors iden,fica,on (using outlier detec,on)
List of
categories
documents stream
Supervised
Learning System
Novel Categories Detector
Using COD-Means
Crowdsourcing
task generator
Emerging novel categories
Crowdsourcing tasks to
be labeled by crowd
An expert
Crowd workers
Crowd/machine classified items.
(Machine classified items with
confidence score >= 0.90)
Incoming uncategorized
documents stream
Machine categorized items
(item, category and machine
confidence score) triplet
Refined training set
Human
labels
Labels
1
2
3
4
106. Conclusions
• InformaBon bestows power for disaster response
– People need informa,on as much as water, shelter, and food
– Disasters are unavoidable, but planning can lessen their effects
• Social media as Bme-criBcal informaBon source
– Early warnings, event detec,on, event monitoring
– Availability of informa,on opens new opportuni,es
• ArBficial Intelligence for Social Good
– Applied research at its best
– AI + humans-in-the-loop can enable rapid crisis response
– AI techniques useful for:
• Situa,onal awareness
• Ac,onable informa,on extrac,on
• Summariza,on