COLLNET2019
15th International Conference on Webometrics, Informetrics and Scientometrics (WIS) & 20th COLLNET Meeting 2019
Dalian, China
5 - 8 November 2019
The conference ended on 08 November 2019
Important Dates
Abstract Submission Deadline
31st May 2019
Abstract Acceptance Notification
31st July 2019
Final Abstract / Full Paper Deadline
15th August 2019
About COLLNET2019
The main focus of this conference is laid on scientific collaboration, quantitative aspects of communication in science, technology and science policy, the science of science as well as the integration of qualitative and quantitative approaches in evaluative contexts. In particular, the conference aims to contribute to evidence-based knowledge about scientific research and practices, which, in turn, is expected to further provide input to institutional, regional, national and international policy-making in research and innovation.
Topics
Library science, Scientometrics, Bibliometrics, WebometricsCall for Papers
We welcome contributions on theoretical, methodological and applied topics covered by the conference, which will comprise the following issues:
- New research trends in Scientometrics, Informetrics and Webometrics
- New research trends in Science of Science
- Models and measurement of scholarly and wider scientific communication
- Altmetrics & social-media metrics
- Gender and diversity
- Mobility and migration of scientists
- New trends in technology, economic and policy relevant contexts
- S&T policy and strategies
- New methods in research assessment
- Quantitative and qualitative assessment: bibliometrics and peer review
- Quantitative analysis of S&T innovation
- Patent analysis and the science–technology linkage
- Mapping of science and visualization techniques
- Mapping and visualization of the cognitive structure of science
- Community and topic detection
- Analysis of complex networks
- International and cross-disciplinary collaboration network
- Big Data and Open Science
- Open access, open data and open source
- Open review and open science and the academic reward system
- Scientometrics and Big Data: Data analytics and data mining
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