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

Large-scale diversity estimation through surname origin inference

The study of surnames as both linguistic and geographical markers of the past has proven valuable in several research fields spanning from biology and genetics to demography and social mobility. This article builds upon the existing literature to conceive and develop a surname origin classifier based on a data-driven typology. This enables us to explore a methodology to describe large-scale estimates of the relative diversity of social groups, especially when such data is scarcely available. We subsequently analyze the representativeness of surname origins for 15 socio-professional groups in France

From evidence-based research to practice-based evidence : disseminating a web-based computer-tailored workplace sitting intervention through a health promotion organisation

Prolonged sitting has been linked to adverse health outcomes; therefore, we developed and examined a web-based, computer-tailored workplace sitting intervention. As we had previously shown good effectiveness, the next stage was to conduct a dissemination study. This study reports on the dissemination efforts of a health promotion organisation, associated costs, reach achieved, and attributes of the website users. The organisation systematically registered all the time and resources invested to promote the intervention. Website usage statistics (reach) and descriptive statistics (website users' attributes) were also assessed. Online strategies (promotion on their homepage; sending e-mails, newsletters, Twitter, Facebook and LinkedIn posts to professional partners) were the main dissemination methods. The total time investment was 25.6 h, which cost approximately 845 EUR in salaries. After sixteen months, 1599 adults had visited the website and 1500 (93.8%) completed the survey to receive personalized sitting advice. This sample was 38.3 +/- 11.0 years, mainly female (76.9%), college/university educated (89.0%), highly sedentary (88.5% sat >8 h/day) and intending to change (93.0%) their sitting. Given the small time and money investment, these outcomes are positive and indicate the potential for wide-scale dissemination. However, more efforts are needed to reach men, non-college/university educated employees, and those not intending behavioural change

Study protocol : responding to the needs of patients with IgA nephropathy, a social media approach

Background IgA nephropathy is the most common cause of glomerulonephritis in the Western world and predominantly affects young adults. Demographically these patients are the biggest users of social media. With increasing numbers of patients turning to social media to seek information and support in dealing with their disease, analysis of social media streams is an attractive modern strategy for understanding and responding to unmet patient need. Methods To identify unmet patient need in this population, a framework analysis will be undertaken of prospectively acquired social media posts from patients with IgA nephropathy, acquired from a range of different social media platforms. In collaboration with patients and members of the clinical multidisciplinary team, resources will be created to bridge gaps in patient knowledge and education identified through social media analysis and returned to patients via social media channels and bespoke websites. Analysis of the impact of these resources will be undertaken with further social media analysis, surveys and focus groups. Conclusions Patients with chronic diseases are increasingly using social networking channels to connect with others with similar diseases and to search for information to help them understand their condition. This project is a 21st century digital solution to understanding patient need and developing resources in partnership with patients, and has wide applicability as a future model for understanding patient needs in a variety of conditions

Towards an understanding of job matching using web data

The thesis explores the feasibility of using web data in labour research in general and of applying these data sources to the study of job matching in particular. Utilizing large-scale data sources, including web surveys and online job vacancies, the thesis aims to identify where the state of the art is and lay methodological, conceptual and analytical foundations for further exploration and research in the area. Formally, the thesis consists of five essays, which either have been or are on the way to be published in scientific journals

Accounting, accountability, social media and big data: Revolution or hype?

Purpose: The purpose of this paper is to outline an agenda for researching the relationship between technology-enabled networks â such as social media and big data â and the accounting function. In doing so, it links the contents of an unfolding area research with the papers published in this special issue of Accounting, Auditing and Accountability Journal. Design/methodology/approach: The paper surveys the existing literature, which is still in its infancy, and proposes ways in which to frame early and future research. The intention is not to offer a comprehensive review, but to stimulate and conversation. Findings: The authors review several existing studies exploring technology-enabled networks and highlight some of the key aspects featuring social media and big data, before offering a classification of existing research efforts, as well as opportunities for future research. Three areas of investigation are identified: new performance indicators based on social media and big data; governance of social media and big data information resources; and, finally, social media and big dataâs alteration of information and decision-making processes. Originality/value: The authors are currently experiencing a technological revolution that will fundamentally change the way in which organisations, as well as individuals, operate. It is claimed that many knowledge-based jobs are being automated, as well as others transformed with, for example, data scientists ready to replace even the most qualified accountants. But, of course, similar claims have been made before and therefore, as academics, the authors are called upon to explore the impact of these technology-enabled networks further. This paper contributes by starting a debate and speculating on the possible research agendas ahead

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

The Australian Complementary Medicine Workforce: A Profile of 1,306 Practitioners from the PRACI Study

© Copyright 2018, Mary Ann Liebert, Inc. 2018. Objectives: This study aims to describe the Australian complementary medicine (CM) workforce, including practice and professional characteristics. Design: National cross-sectional survey. Settings/Location: Australia. Subjects: Any individual who self-identified as a practitioner qualified in any one of 14 CM professions and working in any state or territory of Australia was eligible to participate in the survey. Interventions: A 19-item online survey was developed following a review of existing CM workforce data and in alignment with other CM workforce survey projects in progress at the time. The survey items were presented under three main constructs: demographic characteristics, professional characteristics, and practice characteristics. Statistical analysis: Descriptive statistical analysis, including frequencies and percentages, of multiple choice survey items was used. Open response items were analyzed to determine the mean, standard deviation (SD), minimum, and maximum. The demographic data were evaluated for representativeness based on previously reported CM workforce figures. Results: The survey was completed by 1306 CM practitioners and was found to be nationally representative compared with the most recent registrant data from the Chinese Medicine Board of Australia. Participants primarily practiced in the most populous Australian states and worked in at least one urban clinical location. Most participants held an Advanced Diploma qualification or lower, obtained their qualification ten more years ago, and practiced in a clinical environment alongside at least one other practitioner from another health profession. Participants reported diverse clinical practice specialties and occupational roles. Per week, participants worked an average of 3.7 days and treated 23.6 clients. Conclusions: The results from this survey of practitioners from most complementary professions in Australia provide new insights into the national complementary medicine workforce. Further exploration of the CM workforce is warranted to inform all who provide patient care and develop health policy for better patient and public health outcomes