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      Retrospectively evidencing research impact using online data mining

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          Abstract

          Higher education institutions in the UK and elsewhere are under increasing pressure to measure the impact of their research, which can include how the research has increased scientific engagement among the general public. For various reasons, the need for evidence can arise months, or even years, after a particular research discovery has been made. Furthermore, the right kind of evidence is needed to indicate genuine changes in behaviour, knowledge or attitudes among a given target audience, which can be difficult to obtain after time has passed. In this article, we present a number of strategies for retrospective evidencing of ‘what happened and who cared’, illustrating their use to measure public engagement with example discoveries from up to five years ago.

          Most cited references11

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          A terrestrial planet candidate in a temperate orbit around Proxima Centauri

          At a distance of 1.295 parsecs, the red dwarf Proxima Centauri (α Centauri C, GL 551, HIP 70890 or simply Proxima) is the Sun's closest stellar neighbour and one of the best-studied low-mass stars. It has an effective temperature of only around 3,050 kelvin, a luminosity of 0.15 per cent of that of the Sun, a measured radius of 14 per cent of the radius of the Sun and a mass of about 12 per cent of the mass of the Sun. Although Proxima is considered a moderately active star, its rotation period is about 83 days (ref. 3) and its quiescent activity levels and X-ray luminosity are comparable to those of the Sun. Here we report observations that reveal the presence of a small planet with a minimum mass of about 1.3 Earth masses orbiting Proxima with a period of approximately 11.2 days at a semi-major-axis distance of around 0.05 astronomical units. Its equilibrium temperature is within the range where water could be liquid on its surface.
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            Scientists on Twitter: Preaching to the choir or singing from the rooftops?

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              Scientific networks on Twitter: Analyzing scientists’ interactions in the climate change debate

              Scientific issues requiring urgent societal actions—such as climate change—have increased the need for communication and interaction between scientists and other societal actors. Social media platforms facilitate such exchanges. This study investigates who scientists interact with on Twitter, and whether their communication differs when engaging with actors beyond the scientific community. We focus on the climate change debate on Twitter and combine network analysis with automated content analysis. The results show that scientists interact most intensively with their peers, but also communication beyond the scientific community is important. The findings suggest that scientists adjust their communication style to their audience: They use more neutral language when communicating with other scientists, and more words expressing negative emotions when communicating with journalists, civil society, and politicians. Likewise, they stress certainty more when communicating with politicians, indicating that scientists use language strategically when communicating beyond the scientific community.
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                Author and article information

                Journal
                rfa
                Research for All
                UCL Press (UK )
                2399-8121
                01 March 2022
                : 6
                : 1
                : e06107
                Affiliations
                [1]Department of Physics and Astronomy, Queen Mary University of London, UK
                Author notes
                Author information
                https://orcid.org/0000-0003-4225-0158
                Article
                10.14324/RFA.06.1.07
                7273ac6b-a1f0-4958-8192-4164623da0c0
                Copyright 2022, Chris D. White, Anthony Phillips and Beltran Sajonia-Coburgo-Gotha

                This is an open-access article distributed under the terms of the Creative Commons Attribution Licence (CC BY) 4.0 https://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

                History
                : 28 April 2021
                : 15 December 2021
                Page count
                Figures: 12, Tables: 2, References: 14, Pages: 17
                Categories
                Article

                Assessment, Evaluation & Research methods,Education & Public policy,Educational research & Statistics
                online data mining,behavioural change,public engagement,research impact,evidence

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