Key Messages
Citizen scientists have contributed thousands of reports of skating conditions in Canada.
Variability in reported “skateability” is evident across 10 Canadian cities and the temperature‐skating relationship varies across Canada.
Climate modelling scenarios suggest significant declines in opportunities for outdoor skating across Canada.
Social media applications have become popular methods of online communication, interaction, and social networking. Many people use social media websites and mobile applications, such as Twitter, to create and post personal expressions in public online forums. This online content presents opportunities for using social media as a data source with the potential to improve evaluation of theoretical models of emotional and stressful experiences across various topics and subfields of psychology science and practice. In this article, we discuss emerging information retrieval and analytic methods using social media for ecological momentary assessments of emotion. We describe 2 specific methods we have developed in the context of Twitter and their use in a broader study investigating relationships among people's emotional experiences, their expressions of experiences in social media, their daily geospatial movements and locations, and their stress experiences. We conclude with a discussion of potential applications and ethical considerations for these methods in professional psychology practice and science.
• Citizen science data helped identify key temperature thresholds for building and maintaining outdoor skating rinks. • Since 1942, temperatures are becoming less favourable for building backyard skating rinks in five of the Original Six NHL cities. • Toronto has experienced the most significant loss of skating days. This study conducted linear and change-point analyses of historical trends since 1942 in the length and number of days suitable for skating on backyard rinks in the "Original Six" National Hockey League cities of Boston, Chicago, Detroit, Montreal, New York, and Toronto. Analysis is based on the relationship between ambient air temperatures and the probability of skating, using thresholds identified through the RinkWatch citizen science project. In all cities, coefficient estimates suggest the number of high-probability skating days per winter is declining, with easternmost cities displaying notable declines and growing inter-annual variability in skating days in recent decades. Linear analysis shows a statistically significant decline in Toronto, with a step-change emerging in 1980, after which there is on average one-third fewer skating days compared with preceding decades. The outdoor skating season trends towards later start dates in Boston, Montreal, New York, and Toronto. Future monitoring of outdoor rinks provides an opportunity for engaging the public in identification of winter warming trends that might otherwise be imperceptible, and for raising awareness of the impacts of climate change.
Social media and other forms of volunteered geographic information (VGI) are used frequently as a source of fine-grained big data for research. While employing geographically referenced social media data for a wide array of purposes has become commonplace, the relevant scales over which these data apply to is typically unknown. For researchers to use VGI appropriately (e.g., aggregated to areal units (e.g., neighbourhoods) to elicit key trend or demographic information), general methods for assessing the quality are required, particularly, the explicit linkage of data quality and relevant spatial scales, as there are no accepted standards or sampling controls. We present a data quality metric, the Spatial-comprehensiveness Index (S-COM), which can delineate feasible study areas or spatial extents based on the quality of uneven and dynamic geographically referenced VGI. This scale-sensitive approach to analyzing VGI is demonstrated over different grains with data from two citizen science initiatives. The S-COM index can be used both to assess feasible study extents based on coverage, user-heterogeneity, and density and to find feasible sub-study areas from a larger, indefinite area. The results identified sub-study areas of VGI for focused analysis, allowing for a larger adoption of a similar methodology in multi-scale analyses of VGI.
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