Characterizing Social Media Metrics of Scholarly Papers: The Effect of Document Properties and Collaboration Patterns

A number of new metrics based on social media platforms—grouped under the term “altmetrics”—have recently been introduced as potential indicators of research impact. Despite their current popularity, there is a lack of information regarding the determinants of these metrics. Using publication and citation data from 1.3 million papers published in 2012 and covered in Thomson Reuters’ Web of Science as well as social media counts from Altmetric.com, this paper analyses the main patterns of five social media metrics as a function of document characteristics (i.e., discipline, document type, title length, number of pages and references) and collaborative practices and compares them to patterns known for citations. Results show that the presence of papers on social media is low, with 21.5% of papers receiving at least one tweet, 4.7% being shared on Facebook, 1.9% mentioned on blogs, 0.8% found on Google+ and 0.7% discussed in mainstream media. By contrast, 66.8% of papers have received at least one citation. Our findings show that both citations and social media metrics increase with the extent of collaboration and the length of the references list. On the other hand, while editorials and news items are seldom cited, it is these types of document that are the most popular on Twitter. Similarly, while longer papers typically attract more citations, an opposite trend is seen on social media platforms. Finally, contrary to what is observed for citations, it is papers in the Social Sciences and humanities that are the most often found on social media platforms. On the whole, these findings suggest that factors driving social media and citations are different. Therefore, social media metrics cannot actually be seen as alternatives to citations; at most, they may function as complements to other type of indicators.     

NCI's publication affiliation conundrum: Reframing innovation to incentivize an equitable path for advocate representation

Advocacy engagement has been at the forefront of National Cancer Institute (NCI) efforts to advance scientific discoveries and transform medical interventions. Nonetheless, the journey for advocates has been uneven. Case in Point: NCI publication affiliation rules of engagement pose unique equity challenges while raising questions about structural representation in biomedical research. Abiding by the core rationale that publication affiliation should be tailored to employment status, the NCI has systematically denied research advocate volunteers the opportunity to specifically list NCI as an institutional affiliation on academic publications. Unpacking advocate NCI publication affiliation restrictions and its links with advocacy heritage preservation and convergent science goals poses unique diversity, equity, and inclusion challenges and opportunities. Improving the quality of structural representation in biomedical research requires new theories of action and flexible planning to advance, promote and build capacity for strategic advocacy inclusion and equity within publication affiliation initiatives. Here we highlight several opportunities for how leadership might formulate a radically different vision for NCI's approach. This perspective interrogates the best way forward for ensuring that biomedical employee and volunteer advocate workforce publication affiliation intersections are characterized by increased creativity and representation parity. Imbuing the scientist and clinical researcher archetype with social dimensions, we join NCI critical thinkers in urging employees, funded academics, and volunteer citizen scientists to collectively assume the role as paladins of science and integrity who view the triumphs of making a difference in science alongside the social responsibility of promoting transdisciplinary professionalism and the democratization of science.     

50 Years of Women in Cell Biology: Where have we been? Where are we going?

It’s been 50 years since Women in Cell Biology (WICB) was founded by junior women cell biologists who found themselves neither represented at the American Society for Cell Biology (ASCB) presentations nor receiving the information, mentoring, and sponsorship they needed to advance their careers. Since then, gender parity at ASCB has made significant strides: WICB has become a standing ASCB committee, women are regularly elected president of the ASCB, and half the symposia speakers are women. Many of WICB’s pioneering initiatives for professional development, including career panels, workshops, awards for accomplishments in science and mentoring, and career mentoring roundtables, have been incorporated and adapted into broader “professional development” that benefits all members of ASCB. The time has passed when we can assume that all women benefit equally from progress. By strategically, thoughtfully, and honestly recognizing the challenges to women of the past and today, we may anticipate those new challenges that will arise in the next 50 years. WICB, in collaboration with the ASCB, can lead in data collection and access and can promote diversity, equity, and inclusion. This work will be a fitting homage to the women who, half a century ago, posted bathroom stall invitations to the first Women in Cell Biology meetup.     

The Impact of Funding through the RF President’s Grants for Young Scientists (the field – Medicine) on Research Productivity: A Quasi-Experimental Study and a Brief Systematic Review

The impact of grants on research productivity has been investigated by a number of retrospective studies. The results of these studies vary considerably. The objective of my study was to investigate the impact of funding through the RF President’s grants for young scientists on the research productivity of awarded applicants. The study compared the number of total articles and citations for awarded and rejected applicants who in 2007 took part in competitions for young candidates of science (CoS’s) and doctors of science (DoS’s) in the scientific field of medicine. The bibliometric analysis was conducted for the period from 2003 to 2012 (five years before and after the competition). The source of bibliometric data is the eLIBRARY.RU database. The impact of grants on the research productivity of Russian young scientists was assessed using the meta-analytical approach based on data from quasi-experimental studies conducted in other countries. The competition featured 149 CoS’s and 41 DoS’s, out of which 24 (16%) and 22 (54%) applicants, respectively, obtained funding. No difference in the number of total articles and citations at baseline, as well as in 2008–2012, for awarded and rejected applicants was found. The combination of data from the Russian study and other quasi-experimental studies (6 studies, 10 competitions) revealed a small treatment effect – an increase in the total number of publications over a 4–5-year period after the competition by 1.23 (95% CI 0.48–1.97). However, the relationship between the number of total publications published by applicants before and after the competition revealed that this treatment effect is an effect of the “maturation” of scientists with a high baseline publication activity – not of grant funding.     

The data‐index: An author‐level metric that values impactful data and incentivizes data sharing

Author‐level metrics are a widely used measure of scientific success. The h‐index and its variants measure publication output (number of publications) and research impact (number of citations). They are often used to influence decisions, such as allocating funding or jobs. Here, we argue that the emphasis on publication output and impact hinders scientific progress in the fields of ecology and evolution because it disincentivizes two fundamental practices: generating impactful (and therefore often long‐term) datasets and sharing data. We describe a new author‐level metric, the data‐index, which values both dataset output (number of datasets) and impact (number of data‐index citations), so promotes generating and sharing data as a result. We discuss how it could be implemented and provide user guidelines. The data‐index is designed to complement other metrics of scientific success, as scientific contributions are diverse and our value system should reflect that both for the benefit of scientific progress and to create a value system that is more equitable, diverse, and inclusive. Future work should focus on promoting other scientific contributions, such as communicating science, informing policy, mentoring other scientists, and providing open‐access code and tools.     

Meeting report: Ocean ‘omics science,technology and cyberinfrastructure: current challenges and future requirements (August 20-23, 2013)

The National Science Foundation’s EarthCube End User Workshop was held at USC Wrigley Marine Science Center on Catalina Island, California in August 2013. The workshop was designed to explore and characterize the needs and tools available to the community that is focusing on microbial and physical oceanography research with a particular emphasis on ‘omic research. The assembled researchers outlined the existing concerns regarding the vast data resources that are being generated, and how we will deal with these resources as their volume and diversity increases. Particular attention was focused on the tools for handling and analyzing the existing data, on the need for the construction and curation of diverse federated databases, as well as development of shared, interoperable, “big-data capable” analytical tools. The key outputs from this workshop include (i) critical scientific challenges and cyber infrastructure constraints, (ii) the current and future ocean ‘omics science grand challenges and questions, and (iii) data management, analytical and associated and cyber-infrastructure capabilities required to meet critical current and future scientific challenges. The main thrust of the meeting and the outcome of this report is a definition of the ‘omics tools, technologies and infrastructures that facilitate continued advance in ocean science biology, marine biogeochemistry, and biological oceanography.     

Systematic Differences in Impact across Publication Tracks at PNAS

Background

Citation data can be used to evaluate the editorial policies and procedures of scientific journals. Here we investigate citation counts for the three different publication tracks of the Proceedings of the National Academy of Sciences of the United States of America (PNAS). This analysis explores the consequences of differences in editor and referee selection, while controlling for the prestige of the journal in which the papers appear.

Methodology/Principal Findings

We find that papers authored and “Contributed” by NAS members (Track III) are on average cited less often than papers that are “Communicated” for others by NAS members (Track I) or submitted directly via the standard peer review process (Track II). However, we also find that the variance in the citation count of Contributed papers, and to a lesser extent Communicated papers, is larger than for direct submissions. Therefore when examining the 10% most-cited papers from each track, Contributed papers receive the most citations, followed by Communicated papers, while Direct submissions receive the least citations.

Conclusion/Significance

Our findings suggest that PNAS “Contributed” papers, in which NAS–member authors select their own reviewers, balance an overall lower impact with an increased probability of publishing exceptional papers. This analysis demonstrates that different editorial procedures are associated with different levels of impact, even within the same prominent journal, and raises interesting questions about the most appropriate metrics for judging an editorial policy''s success.     

Three research priorities for just and sustainable urban systems: Now is the time to refocus

Now is the time to refocus efforts in urban research and design. A changing climate and extreme weather events are presenting unique challenges to urban systems around the world. These challenges illuminate the social barriers that accompany disruptive events such as resource inequities and injustices. In this perspective, we provide three research priorities for just and sustainable urban systems that help to address these matters. The three research priorities are: (1) social equity and justice, (2) circularity, and (3) digital twins. Conceptual context and future research directions are provided for each. For social equity and justice, the future directions are mandatory equity analysis and inclusionary practices, understanding and reconciling historical injustices, and intentional integration with diverse community stakeholders. For circularity applications, they are better metrics for integration, more robust evaluation frameworks, and dynamic modeling at multiple spatial and temporal scales. Future directions for digital twins include developing principles to reduce complexity, integrating model and system components, and reducing barriers to data access. These research priorities are core to meeting several of the United Nations Sustainable Development Goals (i.e., 1—No Poverty, 8—Decent Work and Economic Growth, 10—Reduced Inequalities, and 11—Sustainable Cities and Communities). Useful social and technical matters are discussed throughout, where we highlight the importance of prioritizing localized research efforts, provide guidance for community-engaged research and co-development practices, and explain how these priorities interact to align with the evolving field of industrial ecology.     

The Distribution of the Asymptotic Number of Citations to Sets of Publications by a Researcher or from an Academic Department Are Consistent with a Discrete Lognormal Model

How to quantify the impact of a researcher’s or an institution’s body of work is a matter of increasing importance to scientists, funding agencies, and hiring committees. The use of bibliometric indicators, such as the h-index or the Journal Impact Factor, have become widespread despite their known limitations. We argue that most existing bibliometric indicators are inconsistent, biased, and, worst of all, susceptible to manipulation. Here, we pursue a principled approach to the development of an indicator to quantify the scientific impact of both individual researchers and research institutions grounded on the functional form of the distribution of the asymptotic number of citations. We validate our approach using the publication records of 1,283 researchers from seven scientific and engineering disciplines and the chemistry departments at the 106 U.S. research institutions classified as “very high research activity”. Our approach has three distinct advantages. First, it accurately captures the overall scientific impact of researchers at all career stages, as measured by asymptotic citation counts. Second, unlike other measures, our indicator is resistant to manipulation and rewards publication quality over quantity. Third, our approach captures the time-evolution of the scientific impact of research institutions.     

The Kardashian index: a measure of discrepant social media profile for scientists

In the era of social media there are now many different ways that a scientist can build their public profile; the publication of high-quality scientific papers being just one. While social media is a valuable tool for outreach and the sharing of ideas, there is a danger that this form of communication is gaining too high a value and that we are losing sight of key metrics of scientific value, such as citation indices. To help quantify this, I propose the ‘Kardashian Index’, a measure of discrepancy between a scientist’s social media profile and publication record based on the direct comparison of numbers of citations and Twitter followers.     

Citing a Data Repository: A Case Study of the Protein Data Bank

The Protein Data Bank (PDB) is the worldwide repository of 3D structures of proteins, nucleic acids and complex assemblies. The PDB’s large corpus of data (> 100,000 structures) and related citations provide a well-organized and extensive test set for developing and understanding data citation and access metrics. In this paper, we present a systematic investigation of how authors cite PDB as a data repository. We describe a novel metric based on information cascade constructed by exploring the citation network to measure influence between competing works and apply that to analyze different data citation practices to PDB. Based on this new metric, we found that the original publication of RCSB PDB in the year 2000 continues to attract most citations though many follow-up updates were published. None of these follow-up publications by members of the wwPDB organization can compete with the original publication in terms of citations and influence. Meanwhile, authors increasingly choose to use URLs of PDB in the text instead of citing PDB papers, leading to disruption of the growth of the literature citations. A comparison of data usage statistics and paper citations shows that PDB Web access is highly correlated with URL mentions in the text. The results reveal the trend of how authors cite a biomedical data repository and may provide useful insight of how to measure the impact of a data repository.     

Use of macroecology to integrate social justice and conservation

Both conservation biology and macroecology are synthetic, and macroecological research consistently has informed the theory and practice of biological conservation. Explicit integration of the macroecology of human systems and natural systems has been rare, but can advance the incorporation of social justice, environmental justice and environmental equity into conservation biology and participatory conservation (inclusion in decision‐making of those who are affected by, or can affect, that decision). The basis of this strong link is the focus of macroecology on the relations of a given biota to environmental patterns and processes, and these patterns and processes can affect humans differentially. Macroecological integration of social justice and conservation generally requires spatial and temporal representation of all variables at resolutions and extents that allow meaningful analyses. This requirement may facilitate clarity about social metrics and norms. To illustrate, we examine applications of macroecology to analysis of the effects of climate change on social justice and biological conservation; relations among climate, violence among humans and conservation; and the response of the spread of disease to social and ecological factors. We believe that macroecology is a means of providing transparent inferences that can inform conservation, health and social policies.     

Long-Distance Interdisciplinarity Leads to Higher Scientific Impact

Scholarly collaborations across disparate scientific disciplines are challenging. Collaborators are likely to have their offices in another building, attend different conferences, and publish in other venues; they might speak a different scientific language and value an alien scientific culture. This paper presents a detailed analysis of success and failure of interdisciplinary papers—as manifested in the citations they receive. For 9.2 million interdisciplinary research papers published between 2000 and 2012 we show that the majority (69.9%) of co-cited interdisciplinary pairs are “win-win” relationships, i.e., papers that cite them have higher citation impact and there are as few as 3.3% “lose-lose” relationships. Papers citing references from subdisciplines positioned far apart (in the conceptual space of the UCSD map of science) attract the highest relative citation counts. The findings support the assumption that interdisciplinary research is more successful and leads to results greater than the sum of its disciplinary parts.     

Ethics in Science

Ethics are a set of moral principles and values a civilized society follows. Doing science with principles of ethics is the bedrock of scientific activity. The society trusts that the results and the projected outcome of any scientific activity is based on an honest and conscientious attempt by the scientific community. However, during the last few decades, there has been an explosion of knowledge and the advent of digital age. We can access the publications of competitors with just a “click”. The evaluation parameters have evolved a lot and are based on impact factors, h-index and citations. There is a general feeling that the scientific community is under a lot of pressure for fulfilling the criteria for upward growth and even retention of the positions held. The noble profession of scientific research and academics has been marred by the temptation to falsify and fabricate data, plagiarism and other unethical practices. Broadly speaking, the breach of ethics involves: plagiarism, falsification of data, redundant (duplicate) publication, drawing far-fetched conclusions without hard data, for early publicity, gift authorship (receiving as well as giving), not giving sufficient attention and consideration to scholars and post-docs as per the norms, self promotion at the cost of team-members, treating colleagues (overall all juniors) in a feudal way and Machiavellianism (cunningness and duplicity in general conduct and push to positions of power and pelf). Misconduct in Indian academics and science is also under a lot of focus. It is important and urgent that science, engineering, and health departments and institutions in our country have in place systems for education and training in pursuit of science with ethics by sound and professional courses in Responsible Conduct of Research. All research and academic institution must have the Office of Ethics for information, guidelines, training and professional oversight of conduct of research with the ethos and ethics of research.     

“自然对人类的贡献”的实现、发展趋势和启示

生物多样性和生态系统服务政府间科学政策平台(IPBES)的目标是加强科学政策对生物多样性和生态系统服务的影响。为了更好地理解和展示IPBES目标的基本要素及其相互关系, 在千年生态系统评估(MA)的基础上, IPBES融合多种知识体系, 不断完善、创新, 逐步形成了以“自然对人类的贡献” (NCP)为核心的概念框架。本文首先梳理了NCP的发展历程, 论述了NCP与生态系统服务的关系, 指出两者均关注人类福祉, 但与生态系统服务不同的是, NCP涵盖了自然对人类生活的消极影响, 强调社会文化因素、传统知识和土著居民的地位以及人与自然共同作用的重要性。其次, 本文阐述了人与自然共同实现NCP进而影响人类良好生活质量的机制, 并分析了NCP大幅下降的全球趋势, 提出世界各国应不断推动生物多样性保护主流化, 增加国际交流与合作, 致力实现“人与自然和谐共生”的2050年愿景。最后, 本文讨论了NCP在IPBES评估和《生物多样性公约》磋商谈判中的应用前景, 为今后NCP理论研究和实践提供科学支持。     

Let's Make Gender Diversity in Data Science a Priority Right from the Start

The emergent field of data science is a critical driver for innovation in all sectors, a focus of tremendous workforce development, and an area of increasing importance within science, technology, engineering, and math (STEM). In all of its aspects, data science has the potential to narrow the gender gap and set a new bar for inclusion. To evolve data science in a way that promotes gender diversity, we must address two challenges: (1) how to increase the number of women acquiring skills and working in data science and (2) how to evolve organizations and professional cultures to better retain and advance women in data science. Everyone can contribute.Every March we celebrate both International Women’s Day and Women’s History Month. These annual celebrations remind us that through our current individual and collective behavior, all stakeholders can influence how gender-diverse our future history is likely to be. This is especially important in data science, an emerging science, technology, engineering, and math (STEM) field that is a critical driver for 21st century innovation.Data science focuses on the extraction of knowledge from data. It is a STEM discipline, but requires skills not yet widely taught in STEM disciplines: Skills in managing large datasets, novel analysis and inference approaches, rigorous statistical analysis, new ways to convey outcomes, and more. A recent McKinsey Report [1] indicates that the United States alone will need 1.5 million more data-savvy professionals and 140,000–190,000 more professionals with deep analytic skills by 2020. Helping to create and nurture a broad pool of individuals with data science skills is critical to addressing this growing need and will require intentional action.The emergent field of data science offers the opportunity to narrow the gender gap in STEM (in which only 13% of the engineering workforce and 25% of the computer and mathematical sciences workforce are women [2]) by making diversity a priority early on. In addition to this being the right thing to do, it is the smart thing to do: studies show that companies with employees characterized by diverse inherent traits (traits you were born with) and acquired traits (traits you gain from experience) are 45% more likely to report a growth in market share over the previous year, and 70% more likely to report capture of a new market [3]. Companies with diverse executive boards show higher returns on equity [4]. In short, diversity is a competitive asset in the private sector. In addition, increased diversity in STEM fields, including data science, is a national research and education priority [5].What better time, with increased focus on data science in the public sector, emerging educational curricula and focus within universities, and greater need within the private sector, to foster greater inclusivity and gender diversity? What can we do now to grow data science in a way that reflects the gender diversity and potential for innovation of the greater society?To evolve data science in a way that makes it a rewarding and sustainable career choice for women, we need to address two challenges: how can we increase the number of women acquiring skills and working in data science, and how can we evolve organizations and professional cultures to better retain and advance women in data science?     

Applying conservation reserve design strategies to define ecosystem monitoring priorities

In an era of unprecedented ecological upheaval, monitoring ecosystem change at large spatial scales and over long‐time frames is an essential endeavor of effective environmental management and conservation. However, economic limitations often preclude revisiting entire monitoring networks at high frequency. We aimed here to develop a prioritization strategy for monitoring networks to select a subset of existing sites that meets the principles of complementarity and representativeness of the whole ecological reality, and maximizes ecological complementarity (species accumulation) and the spatial and environmental representativeness. We applied two well‐known approaches for conservation design, the “minimum set” and the “maximal coverage” problems, using a suite of alpha and beta biodiversity metrics. We created a novel function for the R environment that performs biodiversity metric comparisons and site prioritization on a plot‐by‐plot basis. We tested our procedures using plot data provided by the Terrestrial Ecosystem Research Network (TERN) AusPlots, an Australian long‐term monitoring network of 774 vegetation and soil monitoring plots. We selected 250 plots and 80% of the total species recorded as targets for the maximal coverage and minimum set problems, respectively. We compared the subsets selected by the different biodiversity metrics in terms of complementarity and spatial and environmental representativeness. We found that prioritization based on species turnover (i.e., iterative selection of the most dissimilar plot to a cumulative sample in terms of species replacement) maximized ecological complementarity and spatial representativeness, while also providing high environmental coverage. Species richness was an unreliable metric for spatial representation. Selection based on range‐rarity‐richness was balanced in terms of complementarity and representativeness, whereas its richness‐corrected implementation failed to capture ecological and environmental variation. Prioritization based on species turnover is desirable to cover the maximum variability of the whole network. Synthesis and applications: Our results inform monitoring design and conservation priorities, which can benefit by considering the turnover component of beta diversity in addition to univariate metrics. Our tool is computationally efficient, free, and can be readily applied to any species versus sites dataset, facilitating rapid decision‐making.     

Can Economic Analysis Contribute to Disease Elimination and Eradication? A Systematic Review

Background

Infectious diseases elimination and eradication have become important areas of focus for global health and countries. Due to the substantial up-front investments required to eliminate and eradicate, and the overall shortage of resources for health, economic analysis can inform decision making on whether elimination/eradication makes economic sense and on the costs and benefits of alternative strategies. In order to draw lessons for current and future initiatives, we review the economic literature that has addressed questions related to the elimination and eradication of infectious diseases focusing on: why, how and for whom?

Methods

A systematic review was performed by searching economic literature (cost-benefit, cost-effectiveness and economic impact analyses) on elimination/eradication of infectious diseases published from 1980 to 2013 from three large bibliographic databases: one general (SCOPUS), one bio-medical (MEDLINE/PUBMED) and one economic (IDEAS/REPEC).

Results

A total of 690 non-duplicate papers were identified from which only 43 met the inclusion criteria. In addition, only one paper focusing on equity issues, the “for whom?” question, was found. The literature relating to “why?” is the largest, much of it focusing on how much it would cost. A more limited literature estimates the benefits in terms of impact on economic growth with mixed results. The question of how to eradicate or eliminate was informed by an economic literature highlighting that there will be opportunities for individuals and countries to free-ride and that forms of incentives and/or disincentives will be needed. This requires government involvement at country level and global coordination. While there is little doubt that eliminating infectious diseases will eventually improve equity, it will only happen if active steps to promote equity are followed on the path to elimination and eradication.

Conclusion

The largest part of the literature has focused on costs and economic benefits of elimination/eradication. To a lesser extent, challenges associated with achieving elimination/eradication and ensuring equity have also been explored. Although elimination and eradication are, for some diseases, good investments compared with control, countries’ incentives to eliminate do not always align with the global good and the most efficient elimination strategies may not prioritize the poorest populations. For any infectious disease, policy-makers will need to consider realigning contrasting incentives between the individual countries and the global community and to assure that the process towards elimination/eradication considers equity.     

Editorial Bias in Crowd-Sourced Political Information

The Internet has dramatically expanded citizens’ access to and ability to engage with political information. On many websites, any user can contribute and edit “crowd-sourced” information about important political figures. One of the most prominent examples of crowd-sourced information on the Internet is Wikipedia, a free and open encyclopedia created and edited entirely by users, and one of the world’s most accessed websites. While previous studies of crowd-sourced information platforms have found them to be accurate, few have considered biases in what kinds of information are included. We report the results of four randomized field experiments that sought to explore what biases exist in the political articles of this collaborative website. By randomly assigning factually true but either positive or negative and cited or uncited information to the Wikipedia pages of U.S. senators, we uncover substantial evidence of an editorial bias toward positivity on Wikipedia: Negative facts are 36% more likely to be removed by Wikipedia editors than positive facts within 12 hours and 29% more likely within 3 days. Although citations substantially increase an edit’s survival time, the editorial bias toward positivity is not eliminated by inclusion of a citation. We replicate this study on the Wikipedia pages of deceased as well as recently retired but living senators and find no evidence of an editorial bias in either. Our results demonstrate that crowd-sourced information is subject to an editorial bias that favors the politically active.