Paper: "An Empirical Model For Electronic Submissions To Conferences" by Patrick Flandrin

An Empirical Model For Electronic Submissions To Conferences
Patrick Flandrin

Electronic submission to a conference is a process that is known to evolve nonlinearly in time, with a dramatic increase when approaching the deadline. A model has recently been proposed by Alfi et al. (Nature Physics, 2007) for such a process, and the question of its universality has been raised. This problem is revisited here from a data analysis and modeling point of view, on the basis of a larger data set. A new model is proposed that better describes the total evolution of the process (including saturation) and allows for a running prediction of the total number of submissions.

Its freely available (at the moment) from:
   http://www.worldscinet.com/cgi-bin/jform.cgi?/acs/mkt/free/S0219525910002554.html

CfP: PlosOne, "altmetrics: Tracking scholarly impact on the social Web"

Call for papers: PLoSOneon "altmetrics: Tracking scholarly impact on the social Web"

 Deadline: January 28^th, 2012

Details at: http://altmetrics.org/plosone/ 

The huge increase in scientific output is presenting scholars with a deluge of data. There is growing concern that scholarly output may be swamping traditional mechanisms for both pre-publication filtering (e.g. peer review) and post-publication impact filtering (e.g. the Journal Impact Factor).
Increasing scholarly use of Web 2.0 tools like CiteULike, Mendeley, Twitter, and blogs presents an opportunity to create new filters. Metrics based on a diverse set of social sources could yield broader, richer, and timelier assessments of current and potential scholarly impact. Realizing this, many authors have begun to call for investigation of these metrics under the banner of “altmetrics.” Specifically, altmetrics is the creation and study of new metrics based on the Social Web for analyzing and informing scholarship.

Despite the growing speculation and early exploratory investigation into the value of altmetrics, there remains little concrete, objective research into the properties of these metrics: their validity, their potential value and flaws, and their relationship to established measures. Nor has there been any large umbrella to bring these multiple approaches together.

Following on from a first successful workshop on altmetrics, this collection aims to provide a forum for the dissemination of innovative research on these metrics.

We seek high quality submissions that advance the understanding of the efficacy of altmetrics, addressing research areas including:

• Validated new metrics based on social media.

• Tracking science communication on the Web.

• Relation between traditional metrics and altmetrics including validation and correlation.

• The relationship between peer review and altmetrics.

• Evaluated tools for gathering, analyzing, or disseminating altmetrics.

Special Issue: Modeling Science - Understanding, Forecasting and Communicating The Science System

Special Issue of Scientometrics (2011) vol. 89: pages 347-463 of papers from the workshop ‘‘Modeling Science—Understanding, Forecasting and Communicating The Science System,’’ held in Amsterdam October 6–9, 2009.

Papers:

• Peter Mutschke, Philipp Mayr, Philipp Schaer, and York -- Sure Science Models as Value-Added Services for Scholarly Information Systems
• Serge Galam -- Tailor Based Allocations for Multiple Authorship: A Fractional gh-Index
• Timothy S. Evans, Renaud Lambiotte, and Pietro Panzarasa -- Community Structure and Patterns of Scientific Collaboration in Business and Management
• M. Laura Frigotto and Massimo Riccaboni -- A Few Special Cases: Scientific Creativity and Network Dynamics in the Field of Rare Diseases
• Hanning Guo, Scott Weingart, and Katy Bo ̈rner -- Mixed-Indicators Model for Identifying Emerging Research Areas
• Christopher Watts and Nigel Gilbert -- Does Cumulative Advantage Affect Collective Learning in Science? An Agent-Based Simulation

http://www.springerlink.com/content/a84n3885506h1j00/

Paper: The Promise and Perils of Pre-Publication Review: A Multi-Agent Simulation of Biomedical Discovery Under Varying Levels of Review Stringency

Shrager J (2010) The Promise and Perils of Pre-Publication Review: A Multi-Agent Simulation of Biomedical Discovery Under Varying Levels of Review Stringency. PLoS ONE 5(5): e10782. doi:10.1371/journal.pone.0010782

Abstract:

The Internet has enabled profound changes in the way science is performed, especially in scientific communications. Among the most important of these changes is the possibility of new models for pre-publication review, ranging from the current, relatively strict peer-review model, to entirely unreviewed, instant self-publication. Different models may affect scientific progress by altering both the quality and quantity of papers available to the research community. To test how models affect the community, I used a multi-agent simulation of treatment selection and outcome in a patient population to examine how various levels of pre-publication review might affect the rate of scientific progress. I identified a “sweet spot” between the points of very limited and very strict requirements for pre-publication review. The model also produced a u-shaped curve where very limited review requirement was slightly superior to a moderate level of requirement, but not as large as the aforementioned sweet spot. This unexpected phenomenon appears to result from the community taking longer to discover the correct treatment with more strict pre-publication review. In the parameter regimens I explored, both completely unreviewed and very strictly reviewed scientific communication seems likely to hinder scientific progress. Much more investigation is warranted. Multi-agent simulations can help to shed light on complex questions of scientific communication and exhibit interesting, unexpected behaviors.

Article is at:
   http://www.plosone.org/article/info:doi/10.1371/journal.pone.0010782

Paper: How Citation Boosts Promote Scientific Paradigm Shifts and Nobel Prizes

How Citation Boosts Promote Scientific Paradigm Shifts and Nobel Prizes

by Amin Mazloumian, Young-Ho Eom, Dirk Helbing, Sergi Lozano, and Santo Fortunato
in PLoS One, May 2011

Abstract:
Nobel Prizes are commonly seen to be among the most prestigious achievements of our times. Based on mining several million citations, we quantitatively analyze the processes driving paradigm shifts in science. We find that groundbreaking discoveries of Nobel Prize Laureates and other famous scientists are not only acknowledged by many citations of their landmark papers. Surprisingly, they also boost the citation rates of their previous publications. Given that innovations must outcompete the rich-gets-richer effect for scientific citations, it turns out that they can make their way only through citation cascades. A quantitative analysis reveals how and why they happen. Science appears to behave like a self-organized critical system, in which citation cascades of all sizes occur, from continuous scientific progress all the way up to scientific revolutions, which change the way we see our world. Measuring the “boosting effect” of landmark papers, our analysis reveals how new ideas and new players can make their way and finally triumph in a world dominated by established paradigms. The underlying “boost factor” is also useful to discover scientific breakthroughs and talents much earlier than through classical citation analysis, which by now has become a widespread method to measure scientific excellence, influencing scientific careers and the distribution of research funds. Our findings reveal patterns of collective social behavior, which are also interesting from an attention economics perspective. Understanding the origin of scientific authority may therefore ultimately help to explain how social influence comes about and why the value of goods depends so strongly on the attention they attract.

http://www.plosone.org/article/info:doi%2F10.1371%2Fjournal.pone.0018975

Special Issue of JASSS on Simulating the Social Processes of Science

This special issue is a collection of position papers as to the important issues/approaches pertinent to the project of applying social simulation to the phenomenum of science.  For more details see the first paper which is the editorial/introduction.

Simulating the Social Processes of Science
   Bruce Edmonds, Nigel Gilbert, Petra Ahrweiler and Andrea Scharnhorst

• Modelling Theory Communities in Science
     Petra Ahrweiler
• A Social Process in Science and its Content in a Simulation Program
     Wolfgang Balzer and Klaus Manhart
• Using Social Simulation to Explore the Dynamics at Stake in Participatory Research
     Olivier Barreteau and Christophe Le Page
• Two Challenges in Simulating the Social Processes of Science
     Edmund Chattoe-Brown
• Simulating What?
     Harry Collins
• Two Outline Models of Science: AMS And HAMS
     Jim Doran
• A Brief Survey of Some Relevant Philosophy of Science
     Bruce Edmonds
• Conference Models to Bridge Micro and Macro Studies of Science
     Matthew Francisco, Staša Milojevic and Selma Šabanovic
• Bibliometrics, Stylized Facts and the Way Ahead: How to Build Good Social Simulation Models of Science?
     Matthias Meyer
• Modeling Scientists as Agents. How Scientists Cope with the Challenges of the New Public Management of Science
     Marc Mölders, Robin D. Fink and Johannes Weyer
• Science as a Social System and Virtual Research Environment
     Sergey Parinov and Cameron Neylon
• For an Integrated Approach to Agent-Based Modeling of Science
     Nicolas Payette
• Social Simulation That 'Peers into Peer Review'
     Flaminio Squazzoni and Károly Takács
• The Competition for Attention and the Evolution of Science
     Warren Thorngate, Jing Liu and Wahida Chowdhury
• Toward Multi-Level, Multi-Theoretical Model Portfolios for Scientific Enterprise Workforce Dynamics
     Levent Yilmaz
• Computer Simulation and Emergent Reliability in Science
     Kevin Zollman