A Systematic Identification and Analysis of Scientists on Twitter

Metrics derived from Twitter and other social media---often referred to as altmetrics---are increasingly used to estimate the broader social impacts of scholarship. Such efforts, however, may produce highly misleading results, as the entities that participate in conversations about science on these platforms are largely unknown. For instance, if altmetric activities are generated mainly by scientists, does it really capture broader social impacts of science? Here we present a systematic approach to identifying and analyzing scientists on Twitter. Our method can identify scientists across many disciplines, without relying on external bibliographic data, and be easily adapted to identify other stakeholder groups in science. We investigate the demographics, sharing behaviors, and interconnectivity of the identified scientists. We find that Twitter has been employed by scholars across the disciplinary spectrum, with an over-representation of social and computer and information scientists; under-representation of mathematical, physical, and life scientists; and a better representation of women compared to scholarly publishing. Analysis of the sharing of URLs reveals a distinct imprint of scholarly sites, yet only a small fraction of shared URLs are science-related. We find an assortative mixing with respect to disciplines in the networks between scientists, suggesting the maintenance of disciplinary walls in social media. Our work contributes to the literature both methodologically and conceptually---we provide new methods for disambiguating and identifying particular actors on social media and describing the behaviors of scientists, thus providing foundational information for the construction and use of indicators on the basis of social media metrics

“Tenure can withstand Twitter”: we need policies that promote science communication and protect those who engage

In the age of social media, the professor’s podium has expanded. Cassidy R. Sugimoto argues so too must our policies on science communication and academic freedom. Academic freedom is a right for unfettered freedom to research, but also with an obligation to disseminate that research. Twitter and other social media can be used to fulfill this obligation. What we need now are policies that promote science communication with the public and protect those who engage in this discourse

Tweeting biomedicine: an analysis of tweets and citations in the biomedical literature

Data collected by social media platforms have recently been introduced as a new source for indicators to help measure the impact of scholarly research in ways that are complementary to traditional citation-based indicators. Data generated from social media activities related to scholarly content can be used to reflect broad types of impact. This paper aims to provide systematic evidence regarding how often Twitter is used to diffuse journal articles in the biomedical and life sciences. The analysis is based on a set of 1.4 million documents covered by both PubMed and Web of Science (WoS) and published between 2010 and 2012. The number of tweets containing links to these documents was analyzed to evaluate the degree to which certain journals, disciplines, and specialties were represented on Twitter. It is shown that, with less than 10% of PubMed articles mentioned on Twitter, its uptake is low in general. The relationship between tweets and WoS citations was examined for each document at the level of journals and specialties. The results show that tweeting behavior varies between journals and specialties and correlations between tweets and citations are low, implying that impact metrics based on tweets are different from those based on citations. A framework utilizing the coverage of articles and the correlation between Twitter mentions and citations is proposed to facilitate the evaluation of novel social-media based metrics and to shed light on the question in how far the number of tweets is a valid metric to measure research impact.Comment: 22 pages, 4 figures, 5 table

Theories of Informetrics and Scholarly Communication

Scientometrics have become an essential element in the practice and evaluation of science and research, including both the evaluation of individuals and national assessment exercises. Yet, researchers and practitioners in this field have lacked clear theories to guide their work. As early as 1981, then doctoral student Blaise Cronin published The need for a theory of citing —a call to arms for the fledgling scientometric community to produce foundational theories upon which the work of the field could be based. More than three decades later, the time has come to reach out the field again and ask how they have responded to this call. This book compiles the foundational theories that guide informetrics and scholarly communication research. It is a much needed compilation by leading scholars in the field that gathers together the theories that guide our understanding of authorship, citing, and impact

The role of handbooks in knowledge creation and diffusion: A case of science and technology studies

Genre is considered to be an important element in scholarly communication and in the practice of scientific disciplines. However, scientometric studies have typically focused on a single genre, the journal article. The goal of this study is to understand the role that handbooks play in knowledge creation and diffusion and their relationship with the genre of journal articles, particularly in highly interdisciplinary and emergent social science and humanities disciplines. To shed light on these questions we focused on handbooks and journal articles published over the last four decades belonging to the research area of Science and Technology Studies (STS), broadly defined. To get a detailed picture we used the full-text of five handbooks (500,000 words) and a well-defined set of 11,700 STS articles. We confirmed the methodological split of STS into qualitative and quantitative (scientometric) approaches. Even when the two traditions explore similar topics (e.g., science and gender) they approach them from different starting points. The change in cognitive foci in both handbooks and articles partially reflects the changing trends in STS research, often driven by technology. Using text similarity measures we found that, in the case of STS, handbooks play no special role in either focusing the research efforts or marking their decline. In general, they do not represent the summaries of research directions that have emerged since the previous edition of the handbook.Comment: Accepted for publication in Journal of Informetric

A neural network system for transformation of regional cuisine style

We propose a novel system which can transform a recipe into any selected regional style (e.g., Japanese, Mediterranean, or Italian). This system has two characteristics. First the system can identify the degree of regional cuisine style mixture of any selected recipe and visualize such regional cuisine style mixtures using barycentric Newton diagrams. Second, the system can suggest ingredient substitutions through an extended word2vec model, such that a recipe becomes more authentic for any selected regional cuisine style. Drawing on a large number of recipes from Yummly, an example shows how the proposed system can transform a traditional Japanese recipe, Sukiyaki, into French style

Tweets as impact indicators: Examining the implications of automated bot accounts on Twitter

This brief communication presents preliminary findings on automated Twitter accounts distributing links to scientific papers deposited on the preprint repository arXiv. It discusses the implication of the presence of such bots from the perspective of social media metrics (altmetrics), where mentions of scholarly documents on Twitter have been suggested as a means of measuring impact that is both broader and timelier than citations. We present preliminary findings that automated Twitter accounts create a considerable amount of tweets to scientific papers and that they behave differently than common social bots, which has critical implications for the use of raw tweet counts in research evaluation and assessment. We discuss some definitions of Twitter cyborgs and bots in scholarly communication and propose differentiating between different levels of engagement from tweeting only bibliographic information to discussing or commenting on the content of a paper.Comment: 9 pages, 4 figures, 1 tabl

Age stratification and cohort effects in scholarly communication : a study of social sciences

Aging is considered to be an important factor in a scholar’s propensity to innovate, produce, and collaborate on high quality work. Yet, empirical studies in the area are rare and plagued with several limitations. As a result, we lack clear evidence on the relationship between aging and scholarly communication activities and impact. To this end, we study the complete publication profiles of more than 1000 authors across three fields—sociology, economics, and political science—to understand the relationship between aging, productivity, collaboration, and impact. Furthermore, we analyze multiple operationalizations of aging, to determine which is more closely related to observable changes in scholarly communication behavior. The study demonstrates that scholars remain highly productive across the life-span of the career (i.e., 40 years), and that productivity increases steeply until promotion to associate professor and then remains stable. Collaboration increases with age and has increased over time. Lastly, a scholar’s work obtains its highest impact directly around promotion and then decreases over time. Finally, our results suggest a statistically significant relationship between rank of the scholar and productivity, collaboration, and impact. These results inform our understanding of the scientific workforce and the production of science