Shenmeng Xu

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.

Who, what, why? An exploration of JoVE scientific video publications in tweets

This paper investigates how and why scientific video articles are communicated on Twitter. We use video articles published in the Journal of Visualized Experiments (JoVE) as our objects of study. We harvested tweets from October 2011 to November 2015 that contained one or more JoVE links. These tweets “citing” JoVE articles were analyzed both statistically and qualitatively. In this paper, we present the distribution of these tweets, with a closer look at the affordance use of Twitter including hashtags and mentions. In addition, we conducted a content analysis of the sampled Twitter accounts and tweets. We present the coding schemes and results of both Twitter user accounts and tweets text. In addition to the analysis of the coding results, we discuss the content of the tweets with particular attention to issues including the video/visual feature mentioned, the role of Twitter bots, and self-promotion of different stakeholders in the Twitter communication of JoVE video publications.

Four pitfalls in normalizing citation indicators: An investigation of ESI’s selection of highly cited papers

InCites Essential Science Indicators is becoming increasingly used to identify top-performing research and evaluate the impact of institutes. Unfortunately, our study shows that ESI indicators, as well as other normalized citation indicators, have the following flaws. First, the publication month and the online-to-print delay affect a paper’s probability of becoming a Highly Cited Paper (HCP). Papers published in the earlier months of the year are more likely to accumulate enough citation counts to rank at the top 1% compared with those published in later months of the year. Papers with longer online-to-print delays have an apparent advantage for being selected as HCPs. Research field normalizations lead to the third pitfall. Different research fields have different citation thresholds for HCPs, making research field classification important for a journal. In addition, the uniform thresholds for both articles and reviews in ESI affect the reliability of HCP selection because, on average, reviews tend to have higher citation rates than articles. ESI’s selection of HCPs provides an intuitive feel for the problems of normalized citation impact indicators, such as those provided in InCites and SciVal.