Most measures of networks are based on the nodes, although links are also elementary units in networks and represent interesting social or physical connections. In this work we suggest an option for exploring networks, called the h-strength, with explicit focus on links and their strengths. The h-strength and its extensions can naturally simplify a complex network to a small and concise subnetwork (h-subnet) but retains the most important links with its core structure. Its applications in 2 typical information networks, the paper cocitation network of a topic (the h-index) and 5 scientific collaboration networks in the field of "water resources," suggest that h-strength and its extensions could be a useful choice for abstracting, simplifying, and visualizing a complex network. Moreover, we observe that the 2 informetric models, the Glänzel-Schubert model and the Hirsch model, roughly hold in the context of the h-strength for the collaboration networks.

No abstract

Research funding plays a key role in current science, thus it has become an aggregative interesting level in scientometric analysis. In this work, we try to explore the funding ratios of 21 major countries/territories in social science based on 813,809 research articles collected from the Web of Science and indexed by the Social Sciences Citation Index covering the period from 2009 to 2013. The results show that the funding ratios of sample countries/territories in social science are far below that in natural science and some specific subjects (chemistry, engineering, physics, neurosciences). However, there is a positive correlation between them. The funding ratios of People's Republic of China, Sweden and Japan rank the top 3 (over 30 %). Generally, the funding ratios of the top 1 % and top 10 % highly cited articles are higher than those of the rest of articles, and for most cases, the high funding ratio of all articles is related to the high funding ratio of the highly cited articles.

No abstract

For measuring multilevel impact, we introduce the distributive h-indices, which balance two important components (breadth and strength) of multilevel impact at various citing levels. After exploring the theoretical properties of these indices, we studied two cases: 57 library and information science (LIS) journals and social science research in 38 European countries/territories. Results reveal that there are approximate power-law relations between distributive h-indices and some underlying citation indicators, such as total citations, total citing entities, and the h-index. Distributive h-indices provide comprehensive measures for multilevel impact, and lead to a potential tool for citation analysis, particularly at aggregative levels.