Humanitarian Informatics Approach to Cooperation between Citizens & Organizational Decision Makers

Hemant PurohitHumanitarian Informatics Lab, Information Sciences and Technology

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CADMICS-2016‘Collaboration and Decision Making in Crisis Situations’

Workshop at ACM CSCW 2016

20th Century Connectivity between Citizens and Organizations

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21st Century Connectivity:Information Overload for Organizations

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Scenario: Can Disaster Response Organizations leverage Social Data at Scale?

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20M+ Tweets during #Sandy

HURRICANE SANDY RESPONSE: $60+ Bln in damage

Operational Implications of messages:Does anyone know how to donate clothes to hurricane #Sandy victims?

Operational Consequence: Creation of 2nd

Disaster for Resource Management

• Resource demand-supply mismatch

Hurricane Sandy, “Thanks, but no thanks”, NPR, Jan 12 2013http://www.npr.org/2013/01/09/168946170/thanks-but-no-thanks-when-post-

disaster-donations-overwhelm

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DISASTER Event

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Proposed Position: Mine and Manage Social Data along the Coordination and Decision Process Needs

CITIZENSensors

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RESPONSE Organizations

Proposed Position: Humanitarian Informatics Approach

• Cooperative Information System Design between Citizens and Organizations via Web (not limited to crises)

– Address Fundamental Challenges (Malone & Crowston 1990; Schmidt & Bannon 1992)

• Articulation• Awareness

– Organization Characteristics• Structured roles • Pre-established communication, processes, and working norms• More information needs, but less data access & resources

– (Emergent) Online Citizen Community Characteristics• Unstructured roles and responsibilities• No established norms• No specified-given needs, but massive data generation & resources

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Awareness

Challenges(Malone & Crowston 1990; Schmidt & Bannon 1992)

(what) INFORMATION EXTRACTION

(what) INFORMATION CLASSIFICATION

(what) BEHAVIOR MINING, etc.DATA

PROBLEM

DESIGNPROBLEM

ORGANIZATIONS CITIZEN COMMUNITIES

COOPERATIVE INFO SYSTEM

Articulation

- Structured Roles- Defined Tasks:

COLLECT Data, Process, and Make Decisions

- No Structured Roles- No Defined Tasks,

but GENERATE Massive Data

(where) LOCATION PREDICTION

(when) TEMPORAL MODELING

(who) ENGAGEMENT PRIORITIZATION, etc.

ProcessKnowledge

Guidance

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Conclusion

• Start from organizational information needs to create information processing systems for leveraging new information source of citizen communties on social media

• Interdisciplinary Research a necessity to guide information processing, for maximal benefits of humanitarian informatics

• For decision making, Less is More! -- We need to focus on actionable information aligned with process-driven information needs of organizations

• Informatics approach not limited to disaster response, but also applicable for information overload solutions of other humanitarian organizations (e.g., gender-violence policies1)

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1 Purohit et al. (2016). Gender-based violence in 140 characters or fewer: A #BigData case study of Twitter.First Monday, Vol. 21, 1 – 4, January 2016 http://firstmonday.org/ojs/index.php/fm/article/view/6148/5190

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TWITTER: @hemant_ptMAIL: hpurohit@gmu.eduLAB: http://ist.gmu.edu/~hpurohit/humanitarian-informatics-lab.html

Acknowledgement: Respective image sources, and

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