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Renewable energy policies have been recognized as a cornerstone in the transition toward low-emission energy systems. Media reports are an important variable in the policy-making process, interrelating politicians and the public. To understand the changes in media framing of a pioneering renewable energy support act, we collected 6,645 articles fro...
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Background
In the context of the ongoing pandemic, e-learning has become essential to maintain existing medical educational programmes. Evaluation of such courses has thus far been on a small scale at single institutions. Further, systematic appraisal of the large volume of qualitative feedback generated by massive online e-learning courses manuall...
Citations
... In contrast, [37] studied the mental health discourse on Twitter and News and the impact of the moral underpinnings in abating or exacerbating stigma. In [13], structured topic modelling was used to uncover shifts in the emotional content regarding the discussion on renewable energies in German news media. Beyond moral and emotional characteristics, studies on news and communication have employed unsupervised learning and community detection techniques to extract topics from news corpora [26]. ...
This study uses sentiment analysis and the Moral Foundations Theory (MFT) to characterise news content in social media and examine its association with user engagement. We employ Natural Language Processing to quantify the moral and affective linguistic markers. At the same time, we automatically define thematic macro areas of news from major U.S. news outlets and their Twitter followers (Jan 2020 - Mar 2021). By applying Non-Negative Matrix Factorisation to the obtained linguistic features we extract clusters of similar moral and affective profiles, and we identify the emotional and moral characteristics that mostly explain user engagement via regression modelling. We observe that Surprise, Trust, and Harm are crucial elements explaining user engagement and discussion length and that Twitter content from news media outlets has more explanatory power than their linked articles. We contribute with actionable findings evidencing the potential impact of employing specific moral and affective nuances in public and journalistic discourse in today's communication landscape. In particular, our results emphasise the need to balance engagement strategies with potential priming risks in our evolving media landscape.
... An alternative approach is large-scale text analyses using natural language processing, text mining and machine-learning modelling tools (e.g. Dehler-Holland et al., 2021;Otto et al., 2022;Reber et al., 2022;Sodoge et al., 2023;von Nordheim et al., 2019). ...
... Future studies might focus more on this aspect, for example using qualitative content or sentiment analysis. However, given that many of the texts in our three corpora mention sustainable agriculture without having it as their main focus, a sentiment analysis could also be misleading, as it would not be clear whether the identified sentiments are related to sustainable agriculture or some other aspects addressed in the texts (see e.g.Dehler-Holland et al., 2021). This could also help improve how the relative importance of topics is measured (beyond the simple quantitative indicator of relative prevalence that we used).Second, conducting the same analysis in different (EU) countries would allow to verify our findings' cultural robustness and generalizability. ...
Agriculture contributes in several ways to achieving sustainability objectives. However, there is no agreement among different societal groups, such as farmers, consumers and scientists, on what constitutes ‘sustainable agriculture’. These differences affect how the impacts of agricultural production on sustainability objectives is perceived, which solutions are considered and implemented.
In this paper, we investigate the topics discussed under the heading ‘sustainable agriculture’ in German newspapers and agricultural magazines. To this end, we apply topic modelling to extract topics discussed in these two large‐scale text corpora. We complement these with scientific articles as a contrast case. We run separate topic models for each corpus and use the identified topics to compare the patterns qualitatively.
Results reveal heterogeneity in the topics across the three corpora with limited overlaps restricted to topics such as agricultural policy. This supports the assumption that farmers and the broader society in Germany have very different perceptions of sustainable agriculture. A surprising result is the absence of topics related to climate change from the agricultural magazine corpus.
These disparities may create challenges for designing and implementing democratically legitimized policies to promote sustainable agriculture.
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... The media is embedded in its geographical context, forming a mutually reinforcing relationship with locations Broekel, 2021, 2022). Over time, this alignment between media and how it presents specific topics is strengthened due to its need to serve its audience and its ability to choose among media outlets (Garz, 2018;Dehler-Holland et al., 2021, 2022. Although capturing all news data would ideally provide a more comprehensive insight into the local narrative landscape, our study focuses on newspapers with high readership and relevance in Germany (Allcott and Gentzkow, 2017;Deephouse et al., 2017;Hölig et al., 2022). ...
The successful transition toward renewable energies requires public support in areas where their expansion may cause adverse effects. In this context, narratives are crucial as they shape people's perceptions. This article examines the relationship between onshore wind power and related narratives in regions across Germany. We run a series of spatial regression models on regional newspaper data, and our findings suggest that wind-related topics are more prominent and more neutrally (less angrily) framed in regions with more wind turbines. Public attitudes supporting wind energy expansion correlate with the prominence of related topics in regions' narrative landscapes. In contrast, support for anti-wind protests does not seem to correlate with the prominence of wind-energy-related topics in regions with higher wind turbine densities.
... Advances in computer technology and machine learning provide an alternative to computational content analysis techniques, allowing for faster processing of a significantly larger volume of text documents (Burscher et al., 2015;Zamith & Lewis, 2015). This research adopts a novel computational content analysis approach for framing analysis using topic modelling techniques (Dehler-Holland et al., 2021;Nguyen & Hekman, 2022) and aspect-based sentiment analysis (Wu et al., 2021). Topic modelling is conducted using the BERTopic framework library in Python language programming, while sentiment analysis is performed using the Large Language Model GPT-4 from openAI and Claude 2 from ANTHROPIC. ...
Artificial Intelligence (AI) is a transformative force shaping society, and online media plays a pivotal role in shaping public perceptions of it. Given the media’s influence, understanding its framing of recent AI advancements, such as the emergence of Large Language Models (LLMs) like ChatGPT, becomes increasingly critical. These models have revolutionized human-machine interaction and are subject to media narratives that can significantly influence public understanding and policy. This research explores the framing of AI narratives in Indonesian online media through the utilization of topic modelling. The study aims to uncover the dominant narratives and themes surrounding AI, including the nuanced portrayal of LLMs and Chat GPT. Using a dataset of online articles and news pieces on AI in the Indonesian context, topic modelling analysis identifies and analyzes the key topics and sentiments. The findings reveal that Indonesian online media tends to portray AI positively, emphasizing its potential for innovation and economic growth. However, concern about ethical implications and job displacement are also present. These findings provide important insights for AI developers, journalists, and policymakers, highlighting the importance of balanced reporting to shape informed public opinion and ethical AI practices.
... Such a result would factor in metadata and variables that could potentially account for topic prevalence and content. Given its relative speed over manual qualitative coding (26) while offering useful tools for analysis of trends over time as documented by researchers like Dehler-Holland et al. (27) and Idler et al. (28) in their analyses of news articles, STM was chosen to analyse the corpus (Table 1). ...
Introduction
The COVID-19 pandemic caused a widespread public health and financial crisis. The rapid vaccine development generated extensive discussions in both mainstream and social media, sparking optimism in the global financial markets. This study aims to explore the key themes from mainstream media’s coverage of COVID-19 vaccines on Facebook and examine how public interactions and responses on Facebook to mainstream media’s posts are associated with daily stock prices and trade volume of major vaccine manufacturers.
Methods
We obtained mainstream media’s coverage of COVID-19 vaccines and major vaccine manufacturers on Facebook from CrowdTangle, a public insights tool owned and operated by Facebook, as well as the corresponding trade volume and daily closing prices from January 2020 to December 2021. Structural topic modelling was used to analyze social media posts while regression analysis was conducted to determine the impact of Facebook reactions on stock prices and trade volume.
Results
10 diverse topics ranging from vaccine trials and their politicization (note: check that we use American spelling throughout), to stock market discussions were found to evolve over the pandemic. Although Facebook reactions were not consistently associated with vaccine manufacturers’ stock prices, ‘Haha’ and ‘Angry’ reactions showed the strongest association with stock price fluctuations. In comparison, social media reactions had little observable impact on trading volume.
Discussion
Topics generated reflect both actual events during vaccine development as well as its political and economic impact. The topics generated in this study reflect both the actual events surrounding vaccine development and its broader political and economic impact. While we anticipated a stronger correlation, our findings suggest a limited relationship between emotional reactions on Facebook and vaccine manufacturers’ stock prices and trading volume. We also discussed potential technical enhancements for future studies, including the integration of large language models.
... Much of the previous NLP-powered energy transition research has focused on using unsupervised machine learning methods, specifically topic modeling, to uncover latent topics in the material [Dehler-Holland et al., 2021;Repo et al., 2021;Rizzoli et al., 2024;Saheb et al., 2022;Tie and Zhu, 2022]. Alternatively, dictionary-based NLP has been employed to analyse specific aspects of data, such as gender perspectives [Carroll et al., 2024], involvement of startups in renewable energy [Singh et al., 2021], and renewable energy investor sentiment [Herrera et al., 2022]. ...
... To slow down climate change, policymakers around the world are pushing for faster technology implementation referring to renewable energy (Dehler-Holland et al., 2020). A widespread acceptance of policies supporting renewable energy is crucial for the success of the transition to a sustainable energy system (Zawadzki et al., 2022). ...
Environmental problems, global climate change, and democracy are related phenomena. Global climate change, which shows up as weather extremes and altered rainfall patterns, exacerbates a number of environmental problems, including energy security, deforestation, land use changes, biodiversity loss, soil degradation, and water scarcity. Natural resources, food security, economic activity, and human health together with physical infrastructure are all significantly impacted by climate change. Furthermore, the complicated socioeconomic and cultural dynamics of the area are frequently overlooked by the conservation framework, which can hinder conservation efforts by causing disputes with nearby communities. Integrating traditional knowledge and practices, equitable benefit distribution, and local community awareness and participation in conservation programs should all be given top priority in this framework. The region is impacted by transboundary issues such as sea level rise, illegal wildlife and timber trade, changing rainfall patterns, and rising temperatures. Energy security in democracies necessitates the viability of legislative measures pertaining to carbon prices and caps, which are politically difficult due to higher emission taxes and limits. Democracy in carbon/energy demands using renewable biobased feedstocks while allowing for public choice and participation. A thorough conservation framework considering the region’s distinct socioeconomic and cultural features must be created to address these issues. Therefore, it is worthwhile to study the raising awareness by global mass media in several policy frameworks and conservation, climate change impacts on vulnerable communities, inadequate funding for conservation programs, weak implementation together with enforcement of environmental regulations, insufficient coordination among different agencies and stakeholders, regional and transboundary international cooperation, and energy security with emphasis on North-East India to ensure the United Nations Sustainable development goals. In order to combat global climate change in democracies, the chapter focuses on environmental issues including energy democracy and the role of mass media in fostering public awareness, advocating for public policy, rallying support, and facilitating action. A framework pertaining to a democratic and inclusive climate change response is also presented in this chapter, with a focus on North-East India.
... Another frame includes ecological and social problems, as well as accusations against actors who promote the use of renewable energies. Further studies show that the portrayal of renewable energy in media coverage is often shaped by economic frames [35,36], and that elite groups of actors from industry, politics, and state bodies often dominate the discourse, whereas the views of environmental organizations and civil society are underrepresented. Sanderink [37] compared the framing of renewable energy by different energy institutions. ...
Background
Different actors use Instagram to mobilize for their cause and to communicate strategically in terms of their interests in the energy transition. Against this background, our study analyzes how the energy transition is framed on Instagram, that is, which aspects of the energy transition are particularly highlighted and emphasized by specific actor groups. Furthermore, we study the visual representations of the energy transition on Instagram, especially the text–image relation.
Methods
To answer the research questions a quantitative content analysis of 907 Instagram posts dealing with the energy transition posted between January 5 and January 16, 2022 was conducted.
Results
The results show that the communication about the energy transition on Instagram is carried out by a multitude of different groups of actors, especially the economic actors. Communication about renewable energy on Instagram is generally optimistic and in support of the energy transition.
Conclusions
Overall our results speak for a lively interest in renewable energies on Instagram. This is also interesting regarding future communication activities, as the young user group of Instagram, can be encouraged to act by suggesting concrete action alternatives for how everyone can commit to a fast and successful energy transition
... Given variation in the length and style of legislative documents, percentage by frame category was used for each state as the primary metric for the findings, calculated as the number of frames in each category divided by the total frames for that state. The percentage of total frames shows the prominence of frames in each state, often termed the prevalence in framing studies, including those using structural topic modeling software (Dehler-Holland et al., 2021;Roberts et al., 2014). The prevalence (or weight) of frames reflects how much policymakers focus on those issues. ...
Renewable portfolio standard (RPS) laws are among the most important climate change policies, requiring a minimum percentage of electricity from clean energy sources. From 2015–2022 in the U.S., eleven states enacted 100 % RPS laws and seven others strengthened their targets. This study examines the issue framing behind these recent RPS laws, which reflects and affects the political context surrounding the policies, people's views, and support among stakeholders. Through coding of policy documents, the study evaluates how policymakers have framed the policies, differences in framing between states with 100 % and non-100 % RPS targets, and variation in framing connected with political party and partisan votes. Surprisingly, given recommendations in the literature to downplay climate issues and emphasize economics, lawmakers predominantly framed 100 % clean energy laws based on climate change. Policymakers that adopted non-100 % RPS laws utilized less climate framing and garnered more Republican Party legislator votes. The results indicate a distinction in framing between more modest and ambitious climate policies, raising a question about the applicability of recommendations urging minimization of climate messaging to transformative climate and clean energy policy efforts. Depending on political conditions, climate framing may be effective for ambitious energy approaches.
... However, the media's framing of renewable energy does not remain the same and, from time to time, its focus can shift from economic and technological aspects to environmental aspects and from negative reports of impacts to positive reports of renewables' environmental benefits [6,7]. An example of such shifts can be provided by Dehler-Holland et al. [26], whose analysis of 6654 newspaper articles indicated that media discourse regarding the German Renewable Energy Act is no longer communicating optimistic technological and industry messages, but has shifted its focus mostly on policy costs. ...
The strong influence of the media could be leveraged for increasing investments in renewable energy sources (RES), which, in turn, assist the transition to a low-carbon energy system that aligns with renewable energy targets. However, it is not known whether media information facilitates citizens interested in investing. Hence, the aim of this study is to support the decision-making of citizens by improving media information about renewable energy investments. Specific objectives are to measure citizen satisfaction with media information about RES investments and to detect the areas that require immediate attention. To that end, 1536 Greek citizens recruited with simple random sampling were administered structured questionnaires and, to analyze citizen satisfaction, multiple criteria satisfaction analysis was applied. According to results, citizens were not satisfied with media information about RES investments, while the lowest satisfaction was recorded for information about available subsidies for RES investments, as well as changes in the institutional framework. This finding has potentially important implications as inadequate information about investments may prevent interested citizens from investing. Given that investment schemes undergo constant changes and that journalists may not be experts in investments, it is recommended to tailor information to citizens’ understanding and that academics and experts provide the media with simplified information material about RES investments.
