Grand Challenges Killer AppsMoon shot SNA IV 1

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Grand Challenges Killer Apps/Moon shot SNA IV. 1

Grand Challenges Killer Apps/Moon shot SNA IV. 1

Killer app-- society • Epidemology (pandemic): sensors for location, interactions, health • Distributed governance:

Killer app-- society • Epidemology (pandemic): sensors for location, interactions, health • Distributed governance: multiple agents responsible for collective outcomes. • Organizational analysis/creativity in organizations: merging and studying massive amount of digitized information within orgs, much of which is relational.

Epidemeology (pandemics) • Sensors (e. g. , cell phones) to understand • • •

Epidemeology (pandemics) • Sensors (e. g. , cell phones) to understand • • • movement and interactions of people. Data from hospitals, schools. How do interactions change as a result of state of person? How do they change (and how does transmission probability change) based on interventions? Massive simulations. Relevant data are enormous, distributed– perhaps with real time needs requiring CI.

Distributed governance • Emergency response– ex post reconstruction and • • diagnosis. Who communicated

Distributed governance • Emergency response– ex post reconstruction and • • diagnosis. Who communicated with whom? (as compared to who should have) Knowledge communities (ex of smoking research) Empower peer to peer networks, create trust, matching system SN theory helps inform interventions. CI both enables distributed governance, serves as instrument, and as mechanism for intervention (see fig)

Online resource/ Prescription Data SNA research community Expt Interventions

Online resource/ Prescription Data SNA research community Expt Interventions

Killer app-- theory • Virtual worlds • ABM • Systemic level/Multilevel analysis • “Global”

Killer app-- theory • Virtual worlds • ABM • Systemic level/Multilevel analysis • “Global” simulations of conflict

Virtual worlds • Virtual worlds: large online worlds in which one can manipulate interactions,

Virtual worlds • Virtual worlds: large online worlds in which one can manipulate interactions, environment. • Lack of rigorous (esp expt) research on large scale collectives.

Agent Based Modeling • Inform assumptions about agent level behavior. . • Validation of

Agent Based Modeling • Inform assumptions about agent level behavior. . • Validation of models– peg to multiple hypotheses re spread, tipping points, differences in local environments.

Systems level/multi level • Little work on systems • Could collect data on many

Systems level/multi level • Little work on systems • Could collect data on many systems (or at least subsystems), examine both individual and system level outcomes.