文章基本信息

标题：Computational Impact Assessment of Social Justice Documentaries
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作者：Jana Diesner ; Jinseok Kim ; Susie Pak 等
期刊名称：Journal of Electronic Publishing
印刷版ISSN：1080-2711
电子版ISSN：1080-2711
出版年度：2014
卷号：17
期号：3
页码：1-15
DOI：10.3998/3336451.0017.306
出版社：University of Michigan Press
摘要：Documentaries are meant to tell a story, that is, to create memory, spark the imagination and support sharing (Rose, 2012). Moreover, documentaries aim to change people’s knowledge and/ or behavior (Barrett & Leddy, 2008). How can we know if a documentary has achieved these goals? We report on a research project where we have been developing, applying and evaluating a theoretically–grounded, empirical and computational solution for assessing the impact of social justice documentaries in a scalable, robust and rigorous fashion. We leverage cutting–edge methods from socio– technical data analytics—namely natural language processing and network analysis—for this purpose. We also built a publicly available software tool (ConText) that supports these routines. In this paper, we focus on the theoretical framework for this project, present our methodology, and provide an illustrative example of the proposed solution.