Xianwen Wang

The open access advantage considering citation, article usage and social media attention

In this study, we compare the difference in the impact between open access (OA) and non-open access (non-OA) articles. 1761 Nature Communications articles published from 1 January 2012 to 31 August 2013 are selected as our research objects, including 587 OA articles and 1174 non-OA articles. Citation data and daily updated article-level metrics data are harvested directly from the platform of nature.com. Data is analyzed from the static versus temporal-dynamic perspectives. The OA citation advantage is confirmed, and the OA advantage is also applicable when extending the comparing from citation to article views and social media attention. More important, we find that OA papers not only have the great advantage of total downloads, but also have the feature of keeping sustained and steady downloads for a long time. For article downloads, non-OA papers only have a short period of attention, when the advantage of OA papers exists for a much longer time.

Science funding and research output: a study on 10 countries

This study reports research on analyzing the impact of government funding on research output. 500,807 SCI papers published in 2009 in 10 countries are collected and analyzed. The results show that, in China, 70.34% of SCI papers are supported by some research funding, among which 89.57% are supported by National Natural Science Foundation of China (NSFC). Average grants per funding-supported paper in China is 2.95, when in the USA the number is 2.93 and in Japan it is 2.40. The results of funding agency analysis show that, China, Germany and Spain are single funding agency dominated countries, while USA, Japan, Canada and Australia are double funding agencies dominated countries, and the source of funding in UK, France and Italy is diversified.

The role of Chinese---American scientists in China---US scientific collaboration: a study in nanotechnology

In this paper, we use bibliometric methods and social network analysis to analyze the pattern of China–US scientific collaboration on individual level in nanotechnology. Results show that Chinese–American scientists have been playing an important role in China–US scientific collaboration. We find that China–US collaboration in nanotechnology mainly occurs between Chinese and Chinese–American scientists. In the co-authorship network, Chinese–American scientists tend to have higher betweenness centrality. Moreover, the series of polices implemented by the Chinese government to recruit oversea experts seems to contribute a lot to China–US scientific collaboration.

Patent co-citation networks of Fortune 500 companies

This paper provides an overview of the progression of technology structure based on patent co-citation networks. Methods of patent bibliometrics, social network analysis and information visualization are employed to analyze patents of Fortune500 companies indexed in Derwent Innovations Index, the largest patent database in the world. Based on the co-citation networks, several main technology groups are identified, including Chemicals, Petroleum Refining, Motor Vehicles, Pharmaceuticals, Electronics, etc. Relationships among the leading companies and technology groups are also revealed.

Exploring scientists’ working timetable: A global survey

In our previous study (Wang et al., 2012), we analyzed scientists’ working timetable of 3 countries, using realtime downloading data of scientific literatures. In this paper, we make a through analysis about global scientists’ working habits. Top 30 countries/territories from Europe, Asia, Australia, North America, Latin America and Africa are selected as representatives and analyzed in detail. Regional differences for scientists’ working habits exists in different countries. Besides different working cultures, social factors could affect scientists’ research activities and working patterns. Nevertheless, a common conclusion is that scientists today are often working overtime. Although scientists may feel engaged and fulfilled about their hard working, working too much still warns us to reconsider the work–life balance.

Usage patterns of scholarly articles on Web of Science: a study on Web of Science usage count

Usage data of scholarly articles provide a direct way to explore the usage preferences of users. Using the “Usage Count” provided by the Web of Science platform, we collect and analyze the usage data of five journals in the field of Information Science and Library Science, to investigate the usage patterns of scholarly articles on Web of Science. Our analysis finds that the distribution of usage fits a power law. And according to the time distribution of usage, researchers prefer to use more recent papers. As to those old papers, citations play an important role in determining the usage count. Highly cited old papers are more likely to be used even a long time after publication.

How far does scientific community look back

How does the published scientific literature used by scientific community? Many previous studies make analysis on the static usage data. In this research, we propose the concept of dynamic usage data. Based on the platform of realtime.springer.com, we have been monitoring and recording the dynamic usage data of Scientometrics articles round the clock. Our analysis find that papers published in recent four years have many more downloads than papers published four years ago. According to our quantitative calculation, papers downloaded on one day have an average lifetime of 4.1 years approximately. Classic papers are still being downloaded frequently even long after their publication. Additionally, we find that social media may reboot the attention of old scientific literature in a short time.

Divergence and convergence: technology-relatedness evolution in solar energy industry

Exploring and measuring technology-relatedness and its collateral technology divergence and convergence, would have far-reaching theoretical significance and academic value on the chain mode of technology development, and also on the mastery of the laws for technology evolution and progress. Taking the patentometric analysis of solar energy technology worldwide as a case, employing the methodology of technology co-classification analysis, choosing two indicators, namely, mean technology co-classification partners (MTCP) and mean technology co-classification index (MTCI), we have analyzed and measured the evolving process of technology-relatedness. The results not only demonstrate in a direct manner the continuously advancing character of solar energy technology in the tensions of technology divergence and convergence, but also reveal quantitatively that, due to the chain reaction of technology-relatedness, technology divergence and technology convergence would tend to evolve in parallel. Through these, it is indicated that technology divergence and technology convergence are two trends which would develop separately, react mutually, and serve as causation for each other, thus making chain progress and continuously pushing forward the innovation, creation and upgrading of technologies. This is a regular phenomenon on condition that the specific technology area is in a status of sustainable development. It still awaits further research on how to verify and reveal the general principles on the interaction between technology divergence and convergence by conducting empirical studies and combining patent analysis.

Chinese elite brain drain to USA: an investigation of 100 United States national universities

In this research, through the complete investigation of 100 American national universities. A list of 3,776 Chinese-American faculties are collected. Analysis is made from five aspects, including regional statistics, institution statistics, gender statistics, position statistics, and discipline statistics. New York, California and Pennsylvania have the most Chinese-American scholars, when the top three universities are The Ohio State University-Columbus, Emory University, and Texas A&M University. The number of male faculties is much greater than female, when the ratio is roughly 7:3. For the position statistics, the ratio of Professor, Associate Professor and Assistant Professor is 2.7:3:4.3. Biology, Medicine and Computer Science are the top three disciplines with the most Chinese-American faculties.

Network structure of scientific collaborations between China and the EU member states

Collaborations between China and the European Union (EU) member states involve not only connections between China and individual countries, but also interactions between the different EU member states, the latter of which is due also to the influence exerted by the EU’s integration strategy. The complex linkages between China and the EU28, as well as among the 28 EU member states, are of great importance for studying knowledge flows. Using co-authorship analysis, this study explores the changes of the network structure between 2000 and 2014. Our results show that EU member states with middle- or low- scientific capacities, in particular those who joined the EU after 2000, have been actively reshaping the network of scientific collaborations with China. The linkages between middle- and low- scientific capacity countries have been tremendously strengthened in the later years. The network positional advantage (measured by the degree of betweenness centrality) has shifted from a few dominant nations to a wider range of countries. We also find that countries like Belgium, Sweden and Denmark are in important positions connecting the relatively low-capacity ‘new’ EU member states with China. The ‘new’ EU member states—that have relatively low scientific capacity—intend to cooperate with China jointly with ‘old’ EU member(s).