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Published, Version of Record (VoR)Open Access via Drexel Libraries Read and Publish Program 2025CC BY V4.0, Open
Conference proceeding
Beyond the Lens: Quantifying the Impact of Scientific Documentaries through Amazon Reviews
Proceedings of the 17th ACM Web Science Conference 2025, pp 413-424
20 May 2025
Featured in Collection : Research Supported by Drexel Libraries' OA Programs
Abstract
Engaging the public with science is critical for a well-informed population. A popular method of scientific communication is documentaries. Once released, it can be difficult to assess the impact of such works on a large scale, due to the overhead required for in-depth audience feedback studies. In what follows, we overview our complementary approach to qualitative studies through quantitative impact and sentiment analysis of Amazon reviews for several scientific documentaries. In addition to developing a novel impact category taxonomy for this analysis, we release a dataset containing 1296 human-annotated sentences from 1043 Amazon reviews for six movies created in whole or part by the Advanced Visualization Lab (AVL). This interdisciplinary team is housed at the National Center for Supercomputing Applications and consists of visualization designers who focus on cinematic presentations of scientific data. Using this data, we train and evaluate several machine learning and large language models, discussing their effectiveness and possible generalizability for documentaries beyond those focused on for this work. Themes are also extracted from our annotated dataset which, along with our large language model analysis, demonstrate a measure of the ability of scientific documentaries to engage with the public.
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Details
- Title
- Beyond the Lens: Quantifying the Impact of Scientific Documentaries through Amazon Reviews
- Creators
- Jill Naiman - University of Illinois Urbana-ChampaignAria Pessianzadeh - Drexel UniversityHanyu Zhao - Duke UniversityA J Christensen - Scientific Imaging and Visualization (United States)Alistair Nunn - ,Shriya Srikanth - Harvard University PressAnushka Gami - University of Illinois Urbana-ChampaignEmma Maxwell - University of Illinois Urbana-ChampaignLouisa Zhang - University of Illinois Urbana-ChampaignSri Nithya Yeragorla - University of Illinois Urbana-ChampaignRezvaneh Rezapour (Corresponding Author) - Drexel University
- Publication Details
- Proceedings of the 17th ACM Web Science Conference 2025, pp 413-424
- Conference
- Websci '25: 17th ACM Web Science Conference 2025
- Series
- ACM Conferences
- Publisher
- Association for Computing Machinery
- Number of pages
- 12
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:001528454600040
- Other Identifier
- 991022053728204721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Information Systems
- Computer Science, Interdisciplinary Applications