Centre for Climate Communication and Data Science

Using Semantic Similarity and Text Embedding to Measure the Social Media Echo of Strategic Communications

Date: March 29, 2023

Authors: Tristan JB Cann, Ben Dennes, Travis Coan, Saffron O'Neill, Hywel TP Williams

Type: Working Paper

Publication: Arxiv

Online discourse covers a wide range of topics and many actors tailor their content to impact online discussions through carefully crafted messages and targeted campaigns. Yet the scale and diversity of online media content make it difficult to evaluate the impact of a particular message. In this paper, we present a new technique that leverages semantic similarity to quantify the change in the discussion after a particular message has been published. We use a set of press releases from environmental organisations and tweets from the climate change debate to show that our novel approach reveals a heavy-tailed distribution of response in online discourse to strategic communications.

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Visual portrayals of fun in the sun in European news outlets misrepresent heatwave risks

Date: Oct. 18, 2022

Authors: Saffron O'Neill, Sylvia Hayes, Nadine Strauβ, Marie‐Noëlle Doutreix, Katharine Steentjes, Joshua Ettinger, Ned Westwood, James Painter

Type: Journal Publication

Publication: The Geographic Journal

The ways in which news media communicate about heatwaves can influence how society conceptualises and addresses heatwave risks. We examined visual news coverage of the 2019 heatwaves in France, Germany, the Netherlands and the UK, using content and visual critical discourse analyses. Many visuals were positively valenced (in contrast to article texts), framing heatwaves as ‘fun in the sun’. The most prevalent type of images in all countries were photographs of people having fun in or by water. When images did depict the danger of heat extremes, people were largely absent. We conclude that this visual framing of heatwaves is problematic: first, by displacing concerns of vulnerability, it marginalises the experiences of those vulnerable to heatwaves; and second, it excludes opportunities for imagining a more resilient future. We conclude with suggestions to diversify the visual discourse on climate change and heatwaves in the news media.

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Heritage site-seeing through the visitor's lens on Instagram

Date: Oct. 3, 2022

Authors: Tania Loke, Yayoi Teramoto, Chico Q. Camargo, Kathryn Eccles

Type: Journal Article

Publication: Journal of Cultural Analytics

English Heritage is a charity that manages over 400 historic sites in the UK, from prehistoric sites to medieval castles, most of them free, non-ticketed, and unstaffed. As such, there is little information about visitor attendance and behaviour in those sites—a challenge common to other non-ticketed heritage sites. In this context, image-based social media such as Instagram appear as a possible solution, as photographs are often central to the tourist experience, and tourists present their imagined audiences with a self-narrative of their trip. Therefore, this study aims to improve our understanding of tourist behaviour in unstaffed heritage sites by analysing publicly available Instagram data. We collect posts on unstaffed English Heritage sites, finding that posting activity concentrates at a few sites. Focusing on 3,979 images each for the top five sites, we analyse image content using pre-trained object detection models. Besides off-the- shelf inference, we fine-tune a model to identify structures from particular heritage sites, and are able to describe the types of photographs taken by visitors in each site, supporting the notion of tourists as performers with the site serving as backdrop. Overall, this study demonstrates a methodology for understanding cultural behaviour at heritage sites using images from social media posts. In addition to recovering the otherwise lost connection between a heritage organisation and its visitors, our methodology can be readily extended to other tourist destinations to understand how visitors interact with and relate to these sites and the objects within them through their photographs.

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Mis- and disinformation studies are too big to fail: Six suggestions for the field’s future

Date: Sept. 20, 2022

Authors: Chico Q. Camargo and Felix Simon

Type: Journal Article

Publication: Harvard Kennedy School (HKS) Misinformation Review

Who are mis-/disinformation studies for? What agenda does the field serve? How can it be improved? While the increase in the attention towards the topic in the last years is healthy, it has also led to an explosion of papers in all directions, and the field has been subject to various criticisms and attacks. In this commentary, we discuss the status and wider impact of the field, raise current challenges, and propose ways ahead for the development of a more critical, interdisciplinary, and rigorous scholarly discipline of mis- and disinformation studies.


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Computer-assisted classification of contrarian claims about climate change

Date: Nov. 16, 2021

Authors: Travis G. Coan, Constantine Boussalis, John Cook & Mirjam O. Nanko

Type: Journal Article

Publication: Scientific Reports

A growing body of scholarship investigates the role of misinformation in shaping the debate on climate change. Our research builds on and extends this literature by (1) developing and validating a comprehensive taxonomy of climate contrarianism, (2) conducting the largest content analysis to date on contrarian claims, (3) developing a computational model to accurately classify specific claims, and (4) drawing on an extensive corpus from conservative think-tank (CTTs) websites and contrarian blogs to construct a detailed history of claims over the past 20 years. Our study finds that the claims utilized by CTTs and contrarian blogs have focused on attacking the integrity of climate science and scientists and, increasingly, has challenged climate policy and renewable energy. We further demonstrate the utility of our approach by exploring the influence of corporate and foundation funding on the production and dissemination of specific contrarian claims.

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