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Computational Impact Assessment of Social Justice Documentaries

Computational Impact Assessment of Social Justice Documentaries. Jana Diesner, Jinseok Kim, Shubhanshu Mishra, Kiumars Soltani, Sean Wilner, Amirhossein Aleyasen The iSchool , Department of Computer Science, Illinois Informatics Institute. Problem Statement: Measuring Impact.

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Computational Impact Assessment of Social Justice Documentaries

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  1. Computational Impact Assessment of Social Justice Documentaries Jana Diesner, Jinseok Kim, Shubhanshu Mishra, Kiumars Soltani, Sean Wilner, AmirhosseinAleyasen The iSchool, Department of Computer Science, Illinois Informatics Institute

  2. Problem Statement: Measuring Impact • Goal of (social justice) documentaries: Storytelling • Create memories, imagination, sharing • Goal of funders and producers: Impact • Evoke change in people’s knowledge and/or behavior • Common approach/ status quo: • Big data (frequency counts) vs. thick data (interviews) • Science: psychological effects of media on individuals • Need: computational, empirical, scalable, rigorous, theory • Q: How can we know if a documentary has what impact? • Generalized: measure impact of information in terms of change • Q: How early in a film’s life cycle can we answer this question? • Prediction models for likely impact trajectories • Here and now usefulness for producers • Strategic allocation of limited resources • Leverage existing social capital

  3. Approach:A story of microscopes and telescopes • Assumption: documentaries produced, screened, watched as part of larger, dynamic ecosystems of stakeholders and information flow • Method: identify, map, monitor, analyze social(stakeholders) and semantic(information) networksto study their structure, functioning and dynamics

  4. This is no computational fishing expedition. We have theory:CoMTIFramework Diesner J, Pak S, Kim J, Soltani K, Aleyasen A (2014) Computational Assessment of the Impact of Social Justice Documentaries. iConference, Berlin, Gemany

  5. Scientific Logic • Ground truth • Transcript • Reality/ Change • Baseline Content Social Structure Social Structure Social Structure Meta Data Meta Data Meta Data Content Content Content • Theme • Movie • Theme Technology: ConText http://context.lis.illinois.edu

  6. Lessons Learned

  7. Thank you! • Acknowledgement: This work is supported by the FORD Foundation, grant 0125-6162. We are also grateful to feedback and advice from Dr. Susie Pak from St. John’s University, Orlando Bagwell, former director of JustFilms at the Ford Foundation, and Joaquin Alvarado from the Center for Investigative Reporting. • For questions, comments, feedback, follow-up: Jana DiesnerEmail: jdiesner@illinois.eduPhone: (412) 519 7576Web: http://people.lis.illinois.edu/~jdiesner

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