Given the prominent position of academia in sustainability studies and sustainability science, it is natural to want to look to universities as models of (or keepers of knowledge about) sustainable practices—including practices related to energy consumption. Nevertheless, there is a long history of and literature on universities failing to implement their own sustainability initiatives. Apart from typical justifications for implementation failure that include budget constraints and financial infeasibility, one of the main obstacles that consistently keeps universities from achieving their own sustainability-related goals is a lack of enforcement. More precisely, universities tend to codify their sustainability-related goals in non-binding declarations that are voluntary. In that respect, failure to achieve a goal does not result in any sort of formal sanction. As such, universities are free to claim a commitment to sustainability in their public communications, without having to consistently and persistently demonstrate that commitment in practice. Situated on this backdrop, the present review paper aims to concisely and selectively stitch together three streams of literature: (1) the rationale for sustainability and, by extension, sustainable energy consumption, in higher education; (2) the current state of sustainability planning and its (in)efficacy in institutions of higher education; and (3) effective practices for reducing energy consumption at scales comparable to university campuses.
Big data provided by social media has been increasingly used in various fields of research including disaster studies and emergency management. Effective data visualization plays a central role in generating meaningful insight from big data. However, big data visualization has been a challenge due to the high complexity and high dimensionality of it. The purpose of this study is to examine how the number and spatial distribution of tweets changed on the day Hurricane Harvey made landfall near Houston, Texas. For this purpose, this study analyzed the change in tweeting activity between the Friday of Hurricane Harvey and a typical Friday before the event.
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