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The Future of Taxpayer-Funded Research: Who Will Control Access to the Results?
This report examines the costs and benefits of increased public access, and proposals to either extend or overturn the NIH policy. It looks at increased public access to research results through the lens of “openness,” with a particular interest in how greater openness affects the progress of science, the productivity of the research enterprise, the process of innovation, the commercialization of research, and economic growth.
URL : http://www.ced.org/images/content/issues/innovation-technology/DCCReport_Final_2_9-12.pdf
Trends in Scholarly Communication and Knowledge Dissemination in the Age of Online Social Media
It is no secret that Online Social Media (OSM) has become mainstream in recent years, and their adoption has skyrocketed. As a result of their growing popularity, numerous studies have been conducted on how the general public is using OSM.
However, very little work has been done on how scholars are using and adapting to these new tools in their professional life. In an attempt to fill this significant gap in the research literature, we recently conducted a comprehensive online survey to discover if, how and why scholars are using these new media for communication and knowledge dissemination.
In particular, we focussed on how academics in the social sciences use social media tools for professional purposes, and the implications that this might have on the future of scholarly communication and publishing practices in the age of online social media.
The Rise of the Knowledge Broker
Knowledge brokers are people or organizations that move knowledge around and create connections between researchers and their various audiences.
This commentary reviews some of the literature on knowledge brokering and lays out some thoughts on how to analyze and theorize this practice.
Discussing the invisibility and interstitiality of knowledge brokers, the author argues that social scientists need to analyze more thoroughly their practices, the brokering devices they use, and the benefits and drawbacks of their double peripherality.
The author also argues that knowledge brokers do not only move knowledge, but they also produce a new kind of knowledge: brokered knowledge.”
URL : http://hal-ensmp.archives-ouvertes.fr/hal-00493794/fr/
Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact
Background
Citations in peer-reviewed articles and the impact factor are generally accepted measures of scientific impact. Web 2.0 tools such as Twitter, blogs or social bookmarking tools provide the possibility to construct innovative article-level or journal-level metrics to gauge impact and influence. However, the relationship of the these new metrics to traditional metrics such as citations is not known.
Objective:
(1) To explore the feasibility of measuring social impact of and public attention to scholarly articles by analyzing buzz in social media, (2) to explore the dynamics, content, and timing of tweets relative to the publication of a scholarly article, and (3) to explore whether these metrics are sensitive and specific enough to predict highly cited articles.
Methods
Between July 2008 and November 2011, all tweets containing links to articles in the Journal of Medical Internet Research (JMIR) were mined. For a subset of 1573 tweets about 55 articles published between issues 3/2009 and 2/2010, different metrics of social media impact were calculated and compared against subsequent citation data from Scopus and Google Scholar 17 to 29 months later. A heuristic to predict the top-cited articles in each issue through tweet metrics was validated.
Results
A total of 4208 tweets cited 286 distinct JMIR articles. The distribution of tweets over the first 30 days after article publication followed a power law (Zipf, Bradford, or Pareto distribution), with most tweets sent on the day when an article was published (1458/3318, 43.94% of all tweets in a 60-day period) or on the following day (528/3318, 15.9%), followed by a rapid decay. The Pearson correlations between tweetations and citations were moderate and statistically significant, with correlation coefficients ranging from .42 to .72 for the log-transformed Google Scholar citations, but were less clear for Scopus citations and rank correlations. A linear multivariate model with time and tweets as significant predictors (P < .001) could explain 27% of the variation of citations. Highly tweeted articles were 11 times more likely to be highly cited than less-tweeted articles (9/12 or 75% of highly tweeted article were highly cited, while only 3/43 or 7% of less-tweeted articles were highly cited; rate ratio 0.75/0.07 = 10.75, 95% confidence interval, 3.4–33.6). Top-cited articles can be predicted from top-tweeted articles with 93% specificity and 75% sensitivity.
Conclusions
Tweets can predict highly cited articles within the first 3 days of article publication. Social media activity either increases citations or reflects the underlying qualities of the article that also predict citations, but the true use of these metrics is to measure the distinct concept of social impact. Social impact measures based on tweets are proposed to complement traditional citation metrics. The proposed twimpact factor may be a useful and timely metric to measure uptake of research findings and to filter research findings resonating with the public in real time.
Citations to Wikipedia in Chemistry Journals: A Preliminary Study
Wikipedia has been the subject of an increasing number of studies. Many of these have focused on the quality of Wikipedia articles and the use of Wikipedia by students. Little research has focused on the use of Wikipedia by scholars. This study helps to fill that gap by examining citations to Wikipedia in chemistry journals from three major publishers over a five year period.
The study reports the number of citations to Wikipedia and describes how Wikipedia is being cited. The results show that, while only a small percentage of all articles contained a citation to Wikipedia, it is in fact being cited as a credible information source in articles in major chemistry journals.
Do age and professional rank influence the order of authorship in scientific publications? Some evidence from a micro-level perspective
Scientific authorship has important implications in science since it reflects the contribution to research of the different individual scientists and it is considered by evaluation committees in research assessment processes.
This study analyses the order of authorship in the scientific output of 1,064 permanent scientists at the Spanish CSIC (WoS, 1994–2004).
The influence of age, professional rank and bibliometric profile of scientists over the position of their names in the byline of publications is explored in three different research areas: Biology and Biomedicine, Materials Science and Natural Resources. There is a strong trend for signatures of younger researchers and those in the lower professional ranks to appear in the first position (junior signing pattern), while more veteran or highly-ranked ones, who tend to play supervisory functions in research, are proportionally more likely to sign in the last position (senior signing pattern).
Professional rank and age have an effect on authorship order in the three fields analysed, but there are inter-field differences. Authorship patterns are especially marked in the most collaboration-intensive field (i.e. Biology and Biomedicine), where professional rank seems to be more significant than age in determining the role of scientists in research as seen through their authorship patterns, while age has a more significant effect in the least collaboration-intensive field (Natural Resources).