Nuclear energy: Twitter data mining for social listening analysis

Knowing the presence, attitude and sentiment of society is important to promote policies and actions that influence the development of different energy sources and even more so in the case of an energy source such as nuclear, which has not been without controversy in recent years. The purpose of this paper was to conduct a social listening analysis of nuclear energy using Twitter data mining. A total of 3,709,417 global tweets were analyzed through the interactions and emotions of Twitter users throughout a crucial year: 6 months before and 6 months after the beginning of Russian invasion of Ukraine and the first attack on the Zaporizhzhia NPP. The research uses a novel approach to combine social network analysis methods with the application of artificial neural network models. The results reveal the digital conversation is influenced by the Russian invasion of Ukraine. However, tweets containing personal opinions of influential people also manage to enter the digital conversation, defining the magnitude and direction of the debate. The digital conversation is not constructed as a public argument. Generally, it is a conversation with non-polarized communities (politics, business, science and media); neither armed conflict or military threats against Zaporizhzhia NPP succeed in rousing anti-nuclear voices, even though these events do modify the orientation of the sentiment in the language used, making it more negative.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature

Does the General Public Share Research on Twitter? A Case Study on the Online Conversation about the Search for a Nuclear Repository in Germany

The search for a final nuclear repository in Germany poses a societal and political issue of high national medial presence and controversy. The German Repository Site Selection Act demands the search to be a “participatory, science-based [...] process”. Also, the repository search combines numerous scientific aspects (e. g., geological analyses, technical requirements) with broad societal implications. For these reasons it constitutes a promising background to analyze the general public’s habits regarding referencing research on Twitter. We collected tweets associated with the conversation around the German nuclear repository search based on keywords. Subsamples of the resulting tweet set are coded regarding sending users’ professional roles and types of hyperlinked content. We found the most vocal group participating in the conversation to be activists and initiatives, while journalists constituted the follower-wise most influential accounts in the sample. Regarding references to scientific content, we found only very few cases of direct links to scholarly publications; however, several kinds of indirect references to academic findings could be identified, e. g., links to paraphrases of studies in news articles or blog posts. Our results indicate participation from a fairly diverse set of users in the observed communication around the German repository search; exchanges of research findings however appear to have happened rarely and been limited to very few particular studies. The findings also illustrate a central problem regarding the expressive power of socialmedia-based altmetrics, namely that a large share of signals indicating a scholar-y work’s influence will not be found by searching for explicit identifiers

Information between Data and Knowledge: Information Science and its Neighbors from Data Science to Digital Humanities

Digital humanities as well as data science as neighboring fields pose new challenges and opportunities for information science. The recent focus on data in the context of big data and deep learning brings along new tasks for information scientist for example in research data management. At the same time, information behavior changes in the light of the increasing digital availability of information in academia as well as in everyday life. In this volume, contributions from various fields like information behavior and information literacy, information retrieval, digital humanities, knowledge representation, emerging technologies, and information infrastructure showcase the development of information science research in recent years. Topics as diverse as social media analytics, fake news on Facebook, collaborative search practices, open educational resources or recent developments in research data management are some of the highlights of this volume. For more than 30 years, the International Symposium of Information Science has been the venue for bringing together information scientists from the German speaking countries. In addition to the regular scientific contributions, six of the best competitors for the prize for the best information science master thesis present their work