Social media in scholarly communication : a review of the literature and empirical analysis of Twitter use by SSHRC doctoral award recipients

This report has been commissioned by the Social Sciences and Humanities Research Council (SSHRC) to analyze the role that social media currently plays in scholarly communication as well as to what extent metrics derived from social media activity related to scholarly content can be applied in an evaluation context. Scholarly communication has become more diverse and open with research being discussed, shared and evaluated online. Social media tools are increasingly being used in the research and scholarly communication context, as scholars connect on Facebook, LinkedIn and Twitter or specialized platforms such as ResearchGate, Academia.edu or Mendeley. Research is discussed on blogs or Twitter, while datasets, software code and presentations are shared on Dryad, Github, FigShare and similar websites for reproducibility and reuse. Literature is managed, annotated and shared with online tools such as Mendeley and Zotero, and peer review is starting to be more open and transparent. The changing landscape of scholarly communication has also brought about new possibilities regarding its evaluation. So-called altmetrics are based on scholarly social media activity and have been introduced to reflect scholarly output and impact beyond considering only peer-reviewed journal articles and citations within them to measure scientific success. This includes the measurement of more diverse types of scholarly work and various forms of impact including that on society. This report provides an overview of how various social media tools are used in the research context based on 1) an extensive review of the current literature as well as 2) an empirical analysis of the use of Twitter by the 2010 cohort of SSHRC Doctoral Award recipients was analyzed in depth. Twitter has been chosen as one of the most promising tools regarding interaction with the general public and scholarly communication beyond the scientific community. The report focuses on the opportunities and challenges of social media and derived metrics and attempts to provide SSHRC with information to develop guidelines regarding the use of social media by funded researchers as well support the informed used of social media metrics

Trends in European Climate Change Perception: Where the Effects of Climate Change go unnoticed

Climate change threatens global impacts in a variety of domains that must be limited by adaptation and mitigation measures. The successful implementation of such policies can strongly benefit from the general public’s cooperation motivated by their own risk perceptions. Public participation can be promoted by tailoring policies to the populations they affect, which in turn results in the need for a deeper understanding of how different communities interact with the issue of climate change. Social media platforms such as the microblogging service Twitter have opened unprecedented opportunities for research on public perception in recent years, offering a continuous stream of user-generated data. Simultaneously, they represent a crucial discursive space in which members of the public develop and discuss their opinions and concerns about climate change. Subsequently, this thesis gains insight into the characteristics of public reactions to individual climate change effects and processes by investing corresponding corpora of tweets spanning a decade. For seven western European countries, the spatial, temporal, and thematic reaction patterns are determined with a further assessment of the drivers behind each finding. Tweets are collected, classified, georeferenced, and clustered using a selection of Geographic Information Retrieval as well as Natural Language Processing methods before being analysed regarding thematic trends in their content, spatial distributions and influences of environmental factors, as well temporal distributions and impacts of real-world events. The findings illustrate diverse climate change perceptions that vary across spatial, temporal, and thematic dimensions. Communities tend to focus more on issues relevant to their local or national environment, leading populations to develop a certain degree of specialisation for these aspects of climate change. This typically coincides with a substantially more domestic discourse on the subject and a decrease in interest for corresponding international events. In a similar sense, the tangibility of an event drives the magnitude of reactions. However, while more tangible events are more frequently recognised and discussed, less tangible events tend to be more frequently attributed to climate change as the public shifts their focus from immediate impacts on the personal scale to impacts on the global scale. Additionally, traditional news media are shown to retain a high level of control over science communication and the climate change discourse on Twitter, likely influencing the public’s perspective on global warming. Individual real-world events such as major climate conferences and scientific releases only occasionally elicit strong public reactions when they are topically related to an event type, whereas global protests can lead to significant discussion across various event types. Inversely, global crises such as the COVID-19 pandemic significantly reduce public concern about climate change processes

Altmetrics and societal impact measurements: Match or mismatch? A literature review

Can alternative metrics (altmetrics) data be used to measure societal impact? We wrote this literature overview of empirical studies in order to find an answer to this question. The overview includes two parts. The first part, “societal impact measurements”, explains possible methods and problems in measuring the societal impact of research, case studies for societal impact measurement, societal impact considerations at funding organizations, and the societal problems that should be solved by science. The second part of the review, “altmetrics”, addresses a major question in research evaluation, which is whether altmetrics are proper indicators for measuring the societal impact of research. In the second part we explain the data sources used for altmetrics studies and the importance of field-normalized indicators for impact measurements. This review indicates that it should be relevant for impact measurements to be oriented towards pressing societal problems. Case studies in which societal impact of certain pieces of research is explained seem to provide a legitimate method for measuring societal impact. In the use of altmetrics, field-specific differences should be considered by applying field normalization (in cross-field comparisons). Altmetrics data such as social media counts might mainly reflect the public interest and discussion of scholarly works rather than their societal impact. Altmetrics (Twitter data) might be especially fruitfully employed for research evaluation purposes, if they are used in the context of network approaches. Conclusions based on altmetrics data in research evaluation should be drawn with caution

Visual abstracts to disseminate research on Twitter: a quantitative analysis

The Web has indisputably changed the way researchers share information. Web-based scholarly communication allows to rapidly disseminate research findings, to reach a broader audience, to transversely connect different contents through hypertext linkages, to update and correct texts if needed, and to integrate multimedia materials. Moreover, it allows interactivity and real-time exchange between authors and readers. Such features are even more evident in the context of the so-called Web 2.0, which involves user-generated content, data sharing, and collaborative efforts. The diffusion of social software and web-based applications has lead to a new use of the Web as a platform for generating, re-purposing and consuming scientific content. Social media brought additional advantages and challenges: they help to fulfill the demand for cheap, instant communication in a context of growing collaborative and interdisciplinary research, but they also, for example, add complexity in terms of quantification of the impact of scientific articles. Nevertheless, researchers are now using social media platforms in every phase of the research lifecycle, from identifying opportunities to disseminating findings. In particular, Twitter, the microblogging platform that allows users to post/publish short messages up to 140 (now 280) characters, has emerged as a powerful tool in scholarly communication. Indeed, it connects researchers around the world (both within and outside one\u2019s research field), giving them the chance to communicate and discuss research findings with the rest of the scientific community, to provide and receive post-publication critiques, and to increase the reach and the impact of their work. Recently, also scientific journals adopted social media, and Twitter in particular, to disseminate research findings published on their pages and websites. In the field of biomedical research, this led to the development of new strategies of dissemination..

A framework to extract biomedical knowledge from gluten-related tweets: the case of dietary concerns in digital era

Journal pre proofBig data importance and potential are becoming more and more relevant nowadays, enhanced by the explosive growth of information volume that is being generated on the Internet in the last years. In this sense, many experts agree that social media networks are one of the internet areas with higher growth in recent years and one of the fields that are expected to have a more significant increment in the coming years. Similarly, social media sites are quickly becoming one of the most popular platforms to discuss health issues and exchange social support with others. In this context, this work presents a new methodology to process, classify, visualise and analyse the big data knowledge produced by the sociome on social media platforms. This work proposes a methodology that combines natural language processing techniques, ontology-based named entity recognition methods, machine learning algorithms and graph mining techniques to: (i) reduce the irrelevant messages by identifying and focusing the analysis only on individuals and patient experiences from the public discussion; (ii) reduce the lexical noise produced by the different ways in how users express themselves through the use of domain ontologies; (iii) infer the demographic data of the individuals through the combined analysis of textual, geographical and visual profile information; (iv) perform a community detection and evaluate the health topic study combining the semantic processing of the public discourse with knowledge graph representation techniques; and (v) gain information about the shared resources combining the social media statistics with the semantical analysis of the web contents. The practical relevance of the proposed methodology has been proven in the study of 1.1 million unique messages from more than 400,000 distinct users related to one of the most popular dietary fads that evolve into a multibillion-dollar industry, i.e., gluten-free food. Besides, this work analysed one of the least research fields studied on Twitter concerning public health (i.e., the allergies or immunology diseases as celiac disease), discovering a wide range of health-related conclusions.SING group thanks CITI (Centro de Investigacion, Transferencia e Innovacion) from the University of Vigo for hosting its IT infrastructure. This work was supported by: the Associate Laboratory for Green Chemistry-LAQV, which is financed by national funds from and the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of [UIDB/50006/2020] and [UIDB/04469/2020] units, and BioTecNorte operation [NORTE010145FEDER000004] funded by the European Regional Development Fund under the scope of Norte2020Programa Operacional Regional do Norte, the Xunta de Galicia (Centro singular de investigacion de Galicia accreditation 2019-2022) and the European Union (European Regional Development Fund - ERDF)- Ref. [ED431G2019/06] , and Conselleria de Educacion, Universidades e Formacion Profesional (Xunta de Galicia) under the scope of the strategic funding of [ED431C2018/55GRC] Competitive Reference Group. The authors also acknowledge the post-doctoral fellowship [ED481B2019032] of Martin PerezPerez, funded by the Xunta de Galicia. Funding for open access charge: Universidade de Vigo/CISUGinfo:eu-repo/semantics/publishedVersio

UNDERSTANDING THE SCHOLARLY COMMUNICATION PROCESS THROUGH DIGITAL TRACES: A STUDY OF TWITTER

Through the lens of the exploratory framework of Digital Trace of Scholarly Acts (DTSA), this dissertation study explored researchers’ activities around scholarly articles on Twitter. Using a mixed-methods design, this study analyzed data collected from a large-scale survey and twenty interviews with researchers on Twitter. The Critical Incident Technique was used as part of the interview study to learn about the full stories behind researchers’ sharing of scholarly articles on Twitter. There were variations in the researcher’s sentiment of opinions on articles they tweeted, retweeted, replied, and liked, based on their demographics. Despite a general positive tendency, researchers’ Twitter activities were associated with different sentiment due to their different perceptions of these activities. Variations were also found in how sharing scholarly articles on Twitter fit into researchers’ scholarly acts workflow with no monolithic pattern. This study contributed to a better understanding of the digital traces left by researchers on Twitter by providing richer descriptions and narratives of their activities. Researchers shared scholarly articles on Twitter for a variety of motivations: networking, promoting, disseminating, commenting, communicating with intended users, acknowledgment, and saving for later reference. The findings particularly shed light on the role of Twitter in communicating research and network building. Investigating the impact of the articles on the researchers led to a better understanding of what types of articles had a higher premium of sharing by researchers on Twitter. Evidence was found to support both the normative theory and the constructivist theory – the categories of impact included connecting, informing, practice-changing, beyond research, and potential impact. However, more than half of the shared articles examined had no impact on the researchers’ own work, indicating that Twitter metrics, even solely based on researchers’ Twitter activities, should not be used as an evaluative metric of the articles shared.Doctor of Philosoph

Altmetrics for Digital Libraries: Concepts, Applications, Evaluation, and Recommendations

The volume of scientific literature is rapidly increasing, which has led to researchers becoming overloaded by the number of articles that they have available for reading and difficulties in estimating their quality and relevance (e.g., based on their research interests). Library portals, in these circumstances, are increasingly getting more relevant by using quality indicators that can help researchers during their research discovery process. Several evaluation methods (e.g., citations, Journal Impact Factor, and peer-reviews) have been used and suggested by library portals to help researchers filter out the relevant articles (e.g., articles that have received high citations) for their needs. However, in some cases, these methods have been criticized, and a number of weaknesses have been identified and discussed. For example, citations usually take a long time to appear, and some articles that are important can remain uncited. With the growing presence of social media today, new alternative indicators, known as “altmetrics,” have been encountered and proposed as complementary indicators to traditional measures (i.e., bibliometrics). They can help to identify the online attention received by articles, which might act as a further indicator for research assessment. One often mentioned advantage of these alternative indicators is, for example, that they appear much faster compared to citations. A large number of studies have explored altmetrics for different disciplines, but few studies have reported about altmetrics in the fields of Economics and Business Studies. Furthermore, no studies can be found so far that analyzed altmetrics within these disciplines with respect to libraries and information overload. Thus, this thesis explores opportunities for introducing altmetrics as new method for filtering relevant articles (in library portals) within the discipline of Economic and Business Studies literature. To achieve this objective, we have worked on four main aspects of investigating altmetrics and altmetrics data, respectively, of which the results can be used to fill the gap in this field of research. (1) We first highlight to what extent altmetric information from the two altmetric providers Mendeley and Altmetric.com is present within the journals of Economics and Business Studies. Based on the coverage, we demonstrate that altmetrics data are sparse in these disciplines, and when considering altmetrics data for real-world applications (e.g., in libraries), higher aggregation levels, such as journal level, can overcome their sparsity well. (2) We perform and discuss the correlations of citations on article and journal levels between different types and sources of altmetrics. We could show that Mendeley counts are positive and strongly correlated with citation counts on both article and journal levels, whereas other indicators such as Twitter counts and Altmetric Attention Score are significantly correlated only on journal level. With these correlations, we could suggest Mendeley counts for Economic and Business Studies journals/articles as an alternative indicator to citations. (3) In conjunction with the findings related to altmetrics in Economics and Business Studies journals, we discuss three use cases derived from three ZBW personas in terms of altmetrics. We investigate the use of altmetrics data for potential users with interests in new trends, social media platforms and journal rankings. (4) We investigated the behavior of economic researchers using a survey by exploring the usefulness of different altmetrics on journal level while they make decisions for selecting one article for reading. According to the user evaluation results, we demonstrate that altmetrics are not well known and understood by the economic community. However, this does not mean that these indicators are not helpful at all to economists. Instead, it brings forward the problem of how to introduce altmetrics to the economic community in the right way using which characteristics (e.g., as visible numbers attached at library records or behind the library’s relevance ranking system). Considering the aforementioned findings of this thesis, we can suggest several forms of presenting altmetric information in library portals, using EconBiz as the proof-of-concept, with the intention to assist both researchers and libraries to identify relevant journals or articles (e.g., highly mentioned online and recently published) for their need and to cope with the information overload

The Design of Interactive Visualizations and Analytics for Public Health Data

Public health data plays a critical role in ensuring the health of the populace. Professionals use data as they engage in efforts to improve and protect the health of communities. For the public, data influences their ability to make health-related decisions. Health literacy, which is the ability of an individual to access, understand, and apply health data, is a key determinant of health. At present, people seeking to use public health data are confronted with a myriad of challenges some of which relate to the nature and structure of the data. Interactive visualizations are a category of computational tools that can support individuals as they seek to use public health data. With interactive visualizations, individuals can access underlying data, change how data is represented, manipulate various visual elements, and in certain tools control and perform analytic tasks. That being said, currently, in public health, simple visualizations, which fail to effectively support the exploration of large sets of data, are predominantly used. The goal of this dissertation is to demonstrate the benefit of sophisticated interactive visualizations and analytics. As improperly designed visualizations can negatively impact users’ discourse with data, there is a need for frameworks to help designers think systematically about design issues. Furthermore, there is a need to demonstrate how such frameworks can be utilized. This dissertation includes a process by which designers can create health visualizations. Using this process, five novel visualizations were designed to facilitate making sense of public health data. Three studies were conducted with the visualizations. The first study explores how computational models can be used to make sense of the discourse of health on a social media platform. The second study investigates the use of instructional materials to improve visualization literacy. Visualization literacy is important because even when visualizations are designed properly, there still exists a gap between how a tool works and users’ perceptions of how the tool should work. The last study examines the efficacy of visualizations to improve health literacy. Overall then, this dissertation provides designers with a deeper understanding of how to systematically design health visualizations

Study on open science: The general state of the play in Open Science principles and practices at European life sciences institutes

Nowadays, open science is a hot topic on all levels and also is one of the priorities of the European Research Area. Components that are commonly associated with open science are open access, open data, open methodology, open source, open peer review, open science policies and citizen science. Open science may a great potential to connect and influence the practices of researchers, funding institutions and the public. In this paper, we evaluate the level of openness based on public surveys at four European life sciences institute