Topic Modeling Uncovers Shifts in Media Framing of the German Renewable Energy Act

Dehler-Holland, Joris; Schumacher, Kira; Fïchtner, Wolf

doi:10.1016/j.patter.2020.100169

Cited by 28 publications

(7 citation statements)

References 81 publications

(167 reference statements)

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“…The resulting topic classification was validated through qualitative examination of randomly selected documents from each of the top-20 topics. The same examination also showed that the topics were indeed corresponding to the theoretical concept of interest -that is, frames, -as we initially expected based on the previous research into other topic modeling techniques since our corpora were thematically focused from the beginning (Dehler-Holland et al, 2021;Maier et al, 2018). Additionally, based on the BERTopic results, we examined the evolution of topic frequency over time for the most popular topics.…”

Section: Data Analysis Rq1: Representation Of the War In Ukraine Thro...mentioning

confidence: 56%

My war is your special operation: Engagement with pro- and anti-regime framing of the war in Ukraine on Russian social media

Urman¹,

Makhortykh²

2022

Preprint

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On 24 February 2022, Russia launched a large-scale invasion of Ukraine which since then has been consistently referred to by the Russian authorities as a special operation and not war. The purpose of this specific framing of the Russian aggression can be attributed to multiple reasons, but among the main advantages it provides to the Kremlin is the emphasis of power inequality between Russia and Ukraine as well as minimizing the concerns of the Russian population about the impact of the war on their lives. However, despite all the Kremlin’s propaganda and censorship efforts, it is still unclear what the dominant framing of the war is among regular Russian internet users and how they engage with different frames used in relation to it. To address this gap, we conducted an automated analysis of over 6 million public posts from VK, the biggest Russian social media platform, published between 14 February 2022 and 24 June 2022 and related to different ways of framing the war as well as the ways users engage with these frames. Our analysis reveals that the invasion was predominantly discussed in connection with the losses in the Russian army, and allusions to WW2 were also common. The users who posted about the war were older than average VK users and tuned in to pro-regime and pro-war content more frequently.

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Section: Data Analysis Rq1: Representation Of the War In Ukraine Thro...mentioning

confidence: 56%

My war is your special operation: Engagement with pro- and anti-regime framing of the war in Ukraine on Russian social media

Urman¹,

Makhortykh²

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…In recent years, the need for a low-cost electricity supply has been repeatedly emphasized by politicians and the media [64,65], after the German electricity price had risen relatively sharply to one of the highest in Europe, partly due to the EEG levy [66,67]. Lauber and Jacobsson [68] criticize this increasingly dominant narrative, which is similarly described by Dehler-Holland et al and Schweiger et al [69,70]. By decision of the then liberal-conservative coalition, energy-intensive companies have been partially exempted from paying the EEG levy on their electricity consumption since 2012 [71], which increases the levy to be paid for all other consumers accordingly.…”

Section: Regimementioning

confidence: 99%

Solar Prosumers in the German Energy Transition: A Multi-Level Perspective Analysis of the German ‘Mieterstrom’ Model

et al. 2021

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The expansion of photovoltaics in German cities has so far fallen short of expectations. The concept of ‘tenant electricity’ (‘Mieterstrom’ in German), in which tenants of a building are supplied with solar power produced on site, offers great potential here. A study on behalf of the German Federal Ministry for Economic Affairs and Energy estimated the number of tenant households with good conditions for solar tenant electricity at 3.8 million. At the same time, the federal tenant electricity promotion scheme has been in place since 2017, but only about 1% of the annual budget has been claimed. The aim of this study is to identify the barriers for and drivers of diffusion of the tenant electricity model. To this end, a qualitative document analysis and a range of semi-structured expert interviews have been conducted. The theoretical framework used to guide the analysis is the multi-level perspective. The main barrier found for tenant electricity diffusion is the legal framework on the regime level, which also leads to high transaction costs of implementing tenant electricity. A social barrier is the inertia of some residents to actively concern themselves with their electricity supply and switch to a tenant electricity contract. Among its drivers are long-term trends such as the increasing electricity demand in urban areas, technical developments like blockchain technology and the increasing deployment of smart meters, and the EU Renewable Energy Directive. As long as the restrictive legal framework prevails, the further diffusion of tenant electricity will remain limited.

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“…Ribeiro et al suggested the public perception assessment methodology to predict the public perception of renewable energy technologies using a regression model, and demonstrated its usefulness for hydro, wind, biomass, and solar energies in Portugal [9]. Dehler-Holland et al developed a structural topic model to perform sentiment analysis for the 6645 newspaper articles on German Renewable Energy Act [10].…”

Section: Ntanos Et Al Conducted a Survey To Understand The Greek Peop...mentioning

confidence: 99%

Development and Application of a Big Data Analysis-Based Procedure to Identify Concerns about Renewable Energy

et al. 2021

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To achieve carbon neutrality by 2050, Korea has been expanding its investment in renewal energy distribution and technology development. However, with this rapid expansion of renewable energy, public concern about it has grown. This study developed and used a big data analysis-based procedure to analyze the questions registered on Naver, the largest portal site in Korea, from 2008 to 2020 to identify public concern over renewable energy. The big data analysis-based procedure consisted of two steps. The first was a frequency analysis to identify the most frequently registered words. The second was to classify questions using term frequency-inverse document frequency (TF-IDF) weight and cosine similarity based on word2vec. The analysis revealed the most frequently registered words related to renewable energy, such as “solar power,” “power generation,” “energy,” and “wind power.” It also revealed the most frequently registered questions, such as those related to solar panel installation, renewable energy generation methods, and certificates. To continue expanding renewable energy, it is becoming increasingly important to understand the public’s concerns and create a method to resolve their objections to renewable energy. It is expected that the procedure in this study may provide relevant insight for the method.

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Topic Modeling Uncovers Shifts in Media Framing of the German Renewable Energy Act

Cited by 28 publications

References 81 publications

My war is your special operation: Engagement with pro- and anti-regime framing of the war in Ukraine on Russian social media

My war is your special operation: Engagement with pro- and anti-regime framing of the war in Ukraine on Russian social media

Solar Prosumers in the German Energy Transition: A Multi-Level Perspective Analysis of the German ‘Mieterstrom’ Model

Development and Application of a Big Data Analysis-Based Procedure to Identify Concerns about Renewable Energy

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