Research using social media on hydroelectricity (Chen, Parkins and Sherren 2018; 2019) initiated a new research interest in culturomics, coined by Michel et al. (2011) who created the Google Ngram viewer, built on the Google Books database, as akin to a microscope or telescope for culture. We have noticed many researchers using social media in superficial ways, bypassing social science, but believe culturomics must emerge from a curiosity about human behavior and cultural trends, satisfied through measuring aspects of cultural output (Sherren et al. 2017b).
We are working now to develop the practice of landscape culturomics, expanding into photo-based and archival datasets, as well as experimenting with machine learning analytical methods, to advance the practice of social impact assessment for landscape change (Sherren et al. 2017a; Jaric et al. 2020), including a recent dykeland case study (Chen et al. 2020). A SSHRC Insight Grant led by my colleague Mike Smit is providing us the venue to do so. That grant includes elements to explore status quo social impact assessment methods for hydroelectricity as a comparison point, including analysis of SIA and media coverage (da Silva, Parkins and Sherren, 2021a; da Silva, Parkins and Sherren, 2021b).
A new project funded by the Ocean Graduate Excellence Network extends this landscape culturomic work from hydroelectricity to coastal adaptation, extending on Chen et al. (2020) . Read more about that project here.
Chen, Y., Sherren, K., Smit, M., and Lee, K. Y. in press. Using social media images as data in social science research. New Media and Society, DOI: 10.1177/14614448211038761 [Free access]
da Silva, G.D.P., Parkins, J. and Sherren, K. 2021. Using news coverage and community-based impact assessments to understand and track social effects using the perspectives of affected people and decisionmakers. Journal of Environmental Management, 298: 113467.
da Silva, G.D.P., Parkins, J. and Sherren, K. 2021. Do methods used in social impact assessment adequately capture impacts? An exploration of the research-practice gap using hydroelectricity in Canada. Energy Research & Social Science, 79: 102188.
Jaric, I., Roll, U., Arlinghaus, R., Belmaker, J., Chen, Y., China, V., Douda, K., Essl, F., Jahning, S. C., Jeschke, J. M., Kalinkat, G., Kalous, L., Ladle, R., Lennox, R. J., Rosa, R., Sbragaglia, V., Sherren, K., Smejkal, M., Soriano-Redondo, A., Souza, A. T., Wolter, C. and Correia, R. A. 2020. Expanding conservation culturomics and iEcology from terrestrial to aquatic realms. PLOS Biology, 18(10): e3000935. [Nice coverage of this piece in Phys.Org]
Chen, Y., Caesemaecker, C., Rahman, H.M.T. and Sherren, K. 2020. Comparing cultural ecosystem service delivery in dykelands and marshes using Instagram: A case of the Cornwallis (Jijuktu’kwejk) River, Nova Scotia, Canada. Ocean and Coastal Management, 193, 105254.
Chen, Y., Parkins, J. R. and Sherren, K. 2019. Leveraging Social Media to Understand Younger People’s Perceptions and Use of Hydroelectric Energy Landscapes, Society and Natural Resources, 32, 1114-1122.
Chen, Y., Parkins, J. R. and Sherren, K. 2018 Using geo-tagged Instagram posts to reveal landscape values around current and proposed hydroelectric dams and their reservoirs Landscape and Urban Planning 170, 283-292.
Sherren, K., Parkins, J. R., Smit, M., Holmlund, M., & Chen, Y. (2017a). Digital archives, big data and image-based culturomics for social impact assessment: Opportunities and challenges. Environmental Impact Assessment Review, 67, 23-30.
Sherren, K., Smit, M., Holmlund, M., Parkins, J. R., & Chen, Y. (2017b). Conservation culturomics should include images and a wider range of scholars. Frontiers in Ecology and the Environment, 15(6), 289-290.
da Silva, G.D.P. 2021. Social impact assessment for hydroelectricity in Canada: a review of methods and monitoring. Unpublished MES thesis, Dalhousie University.
Keshava Pallavi Gone has started an IDPhD to work on the text-based social media data gathered for our case hydroelectricity sites, working closely with fellow IDPhD student Yan Chen.
Gardenio Pimentel da Silva (MES candidate 2019-2021) joined the team to explore existing SIA exploration and monitoring methods in the context of hydroelectricity.
Yan Chen’s MES (2016) was co-funded by SSHRC and the Nova Scotia Research and Innovation Graduate Scholarship, worked on social media monitoring and analysis of Instagram images around hydroelectric sites at Mactaquac and Site C. Her MES thesis is available online. She returned in 2018 to undertake a PhD on the Smit-led project using machine learning to explore image-based data to inform SIA tools.