Digital archives,big data and image-based culturomics for social impact assessment: Opportunities and challenges |
| |
| Institution: | 1. School for Resource and Environmental Studies, Dalhousie University, Halifax, NS B3H 4R2, Canada;2. Department of Resource Economics and Environmental Sociology, University of Alberta, Edmonton, AB T6G 2H1, Canada;3. School of Information Management, Dalhousie University, Halifax, NS B3H 4R2, Canada;4. Department of History, Dalhousie University, Halifax, NS B3H 4R2, Canada;1. Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Cornwall Campus TR10 9EZ, UK;2. Wildfowl & Wetlands Trust, Slimbridge, Gloucester GL2 7BT, UK;3. Royal Society for the Protection of Birds, The Lodge, Sandy, Bedfordshire SG19 2DL, UK;4. Environment and Sustainability Institute, University of Exeter, Cornwall Campus TR10 9EZ, UK;1. University of Illinois at Urbana-Champaign, 1408 West Gregory Drive, 225 Library, MC-522, Urbana, IL 61801, USA;2. School of Information Sciences, The University of Tennessee at Knoxville, 424 Communications Building, 1345 Circle Park Drive, Knoxville, TN 37996, USA;1. Glorious Sun School of Business and Management, Donghua University, Shanghai 210005, China;2. Business Division, Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong |
| |
| Abstract: | Social impact assessment (SIA) is well-established but uses conventional approaches that have become less effective in recent decades, particularly in relation to declining survey response rates and a lack of youth engagement. Images from digital archives and social media sources are poised to advance the research and practice of SIA by transcending text-based methods with insights into changing landscapes, and human engagement with them. This viewpoint describes progress, challenges and cautions toward the development of such tools (defined as culturomics), using hydroelectricity cases to illustrate potential approaches. These tools build on foundational work in a range of disciplines, including the humanities and computer science. We describe necessary advances in machine learning, image digitization, and data aggregation and visualization techniques, as well as ways to ensure that such tools are carefully tested, applied and interpreted. Challenges include the automation, acquisition and management of datasets, and using these tools appropriately and equitably. Critically, culturomics of any kind must not be used as a replacement for engagement with people, but as complementary to inclusive stakeholder engagement. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
