Policy labs in Europe: political innovation, structure and content analysis on Twitter

Recent years have seen a veritable boom in the creation of policy labs. These institution-based innvation laboratories aim to open up the processes of public policy design to the social stakeholders involved. In 2016, the European Union Policy Lab commissioned a report that identified 64 such laboratories in Europe. In the present study, we use network analysis to reveal the structure of the relationships between the 42 of these labs that have a presence on Twitter. We then conduct a content analysis of their tweets to identify the topics of interest. Our results describe a fragmented, country-based network and the principal concepts and key issues addressed by these institutions

Where is the science in Wikipedia? Identification and characterization of scientifically supported contents

This study illustrates the challenges of developing a broad Wikipedia thematic landscape. Particularly the limitations of Wikipedia categories in providing an overview of the thematic areas covered in Wikipedia are shown. The use of WikiProjects is presented as a viable although limited alternative, providing interesting classificatory possibilities. The classification proposed here can be useful for further research on Wikipedia as well as for other researchers who want to identify Wikipedia dynamics in a more aggregated and visual way

The Botization of Science? Large-scale study of the presence and impact of Twitter bots in science dissemination

Twitter bots are a controversial element of the platform, and their negative impact is well known. In the field of scientific communication, they have been perceived in a more positive light, and the accounts that serve as feeds alerting about scientific publications are quite common. However, despite being aware of the presence of bots in the dissemination of science, no large-scale estimations have been made nor has it been evaluated if they can truly interfere with altmetrics. Analyzing a dataset of 3,744,231 papers published between 2017 and 2021 and their associated 51,230,936 Twitter mentions, our goal was to determine the volume of publications mentioned by bots and whether they skew altmetrics indicators. Using the BotometerLite API, we categorized Twitter accounts based on their likelihood of being bots. The results showed that 11,073 accounts (0.23% of total users) exhibited automated behavior, contributing to 4.72% of all mentions. A significant bias was observed in the activity of bots. Their presence was particularly pronounced in disciplines such as Mathematics, Physics, and Space Sciences, with some specialties even exceeding 70% of the tweets. However, these are extreme cases, and the impact of this activity on altmetrics varies by speciality, with minimal influence in Arts & Humanities and Social Sciences. This research emphasizes the importance of distinguishing between specialties and disciplines when using Twitter as an altmetric

The Elon Musk Paradox: Quantifying the Presence and Impact of Twitter Bots on Altmetrics with Focus in Social Sciences

With the rise of Twitter bots in social and political spheres, their implications in scientific communication and altmetrics have become a concern. However, there are no large-scale studies that identify the population of bots and their impact on altmetrics. This quantitative study aims to analyse the presence and impact of Twitter bots in the dissemination of Social Science papers on Twitter and to explore the specific case of Information Science & Library Science (ISLS) as a case study. The overall presence of bots discussing Social Science papers has been found to account for 3.61% of users and 3.85% of tweets. However, this presence and impact is uneven across disciplines, highlighting Criminology & Penology with 12.4% of the mentions made by bots. In the specific case of ISLS, it has been determined by Kendall's correlation that mentions of bots have no impact on altmetrics.Full paper available at: https://dapp.orvium.io/deposits/644235015db3c5af25159230/vie

Tweet my paper: Who handles dissemination on Twitter?

The communication of research results is a task that is not equally distributed among authors. This paper explores how researchers distribute dissemination tasks on Twitter, the main channel for scientific communication. The main goal is to determinate which authorship position is most associated with self-dissemination of papers on Twitter, and whether this pattern is homogeneous across research areas. For Twitter mentions to papers, a large-scale dataset was created by merging Web of Science and Altmetric.com data, while for the identification of scholars on Twitter, an open dataset was used. Our main finding shows that 27% of Twitter users who mention papers are scholars and that only 13% of their mentions were for self-promotion purposes. Likewise, the corresponding author is the main responsible for this dissemination, a role that is mainly carried out by the first author.Full paper available at: https://dapp.orvium.io/deposits/64de4a4995b02025f51d327d/vie

Mapping the backbone of the Humanities through the eyes of Wikipedia

The present study aims to establish a valid method by which to apply the theory of co-citations to Wikipedia article references and, subsequently, to map these relationships between scientific papers. This theory, originally applied to scientific literature, will be transferred to the digital environment of collective knowledge generation. To this end, a dataset containing Wikipedia references collected from Altmetric and Scopus’ Journal Metrics journals has been used. The articles have been categorized according to the disciplines and specialties established in the All Science Journal Classification (ASJC). They have also been grouped by journal of publication. A set of articles in the Humanities, comprising 25 555 Wikipedia articles with 41 655 references to 32 245 resources, has been selected. Finally, a descriptive statistical study has been conducted and co-citations have been mapped using networks and indicators of degree and betweenness centralit

Mapping social media attention in Microbiology: Identifying main topics and actors

This paper aims to map and identify topics of interest within the field of Microbiology and identify the main sources driving such attention. We combine data from Web of Science and Altmetric.com, a platform which retrieves mentions to scientific literature from social media and other non-academic communication outlets. We focus on the dissemination of microbial publications in Twitter, news media and policy briefs. A two-mode network of social accounts shows distinctive areas of activity. We identify a cluster of papers mentioned solely by regional news media. A central area of the network is formed by papers discussed by the three outlets. A large portion of the network is driven by Twitter activity. When analyzing top actors contributing to such network, we observe that more than half of the Twitter accounts are bots, mentioning 32% of the documents in our dataset. Within news media outlets, there is a predominance of popular science outlets. With regard to policy briefs, both international and national bodies are represented. Finally, our topic analysis shows that the thematic focus of papers mentioned varies by outlet. While news media cover the wider range of topics, policy briefs are focused on translational medicine, and bacterial outbreaks

Coverage and distribution of altmetric mentions in Spain: a cross-country comparison in 22 research fields

Since their formal proposal in 2010, various studies have been carried out on altmetrics from different perspectives and at different levels. However, the problem of the country-specific differences found in such studies has not been addressed in depth and considering the wide range of social media sources. This paper presents a cross-country comparison of altmetric coverage between Spain and a selection of 16 countries (EU-15 and the United States) in 22 research fields. All Spanish publications indexed in Web of Science that were published between 2016 and 2020, as well as all mentions of their altmetrics collected on Altmetric.com, were retrieved. The results show that, of the 434,827 Spanish publications considered, 55% are found on Altmetric.com. General altmetric coverage in Spain is similar to that in the rest of Europe and the United States, but it is in areas such as Arts & Humanities and Social Sciences where the lowest levels of coverage are found, although in the case of the latter the publications receive a higher number of mentions. Spanish publications reach a total of 3,569,553 mentions from different social media platforms, but Twitter is the main source of these mentions, accounting for 89%. Differences between research fields are also found, such as Environment & Ecology receiving a higher number of policy mentions

Identifying and characterizing social media communities: a socio‑semantic network approach to altmetrics

Funding for open access charge: Universidad de Granada/CBUA. This work has funded by the Spanish Ministry of Science and Innovation grant number PID2019-109127RB-I00/SRA/10.13039/501100011033. Wenceslao Arroyo-Machado has an FPU Grant (FPU18/05835) from the Spanish Ministry of Universities. Daniel Torres-Salinas is supported by the Reincorporation Programme for Young Researchers from the University of Granada. Nicolas Robinson-Garcia is funded by a Ramon y Cajal grant from the Spanish Ministry of Science and Innovation (REF: RYC2019-027886-I).Altmetric indicators allow exploring and profiling individuals who discuss and share scientific literature in social media. But it is still a challenge to identify and characterize communities based on the research topics in which they are interested as social and geographic proximity also influence interactions. This paper proposes a new method which profiles social media users based on their interest on research topics using altmetric data. Social media users are clustered based on the topics related to the research publications they share in social media. This allows removing linkages which respond to social or personal proximity and identifying disconnected users who may have similar research interests. We test this method for users tweeting publications from the fields of Information Science & Library Science, and Microbiology. We conclude by discussing the potential application of this method and how it can assist information professionals, policy managers and academics to understand and identify the main actors discussing research literature in social media.Spanish Government PID2019-109127RB-I00/SRA/10.13039/501100011033Spanish Ministry of Universities FPU18/05835Ramon y Cajal grant from the Spanish Ministry of Science and Innovation REF: RYC2019-027886-IUniversity of GranadaUniversidad de Granada/CBU

Independent publishers and social networks in the 21st century: the balance of power in the transatlantic Spanish-language book market

The present paper uses Twitter to analyze the current state of the worldwide, Spanish-language, independent publishing market. The main purposes are to determine whether certain Latin American Spanish-language independent publishers function as gatekeepers of World Literature and to analyze the geopolitical structure of this global market, addressing both the Europe-America dialectic and neocolonial practices. After selecting the sample of publishers, we conducted a search for their Twitter profiles and located 131; we then downloaded data from the corresponding Twitter APIs. Finally, we applied social network analysis to study the presence of and interaction between our sample of independent publishers on this social media. Our results provide data-based evidence supporting the hypothesis of some literary critics who suggest that in Latin America, certain publishers act as gatekeepers to the mainstream book market. Therefore, Twitter could be considered a valid source of information to address the independent book market in Spanish. By extension, this approach could be applied to other cultural industries in which small and medium-sized agents develop a digital presence in social media. This paper combines social network analysis and literary criticism to provide new evidence about the Spanish-language book market. It helps validate the aforementioned hypothesis, proposed by literary critics, and opens up new paths along which to pursue an interpretative, comparative analysis