Authors:Mathieu Ouimet, Pierre-Olivier Bédard, and François Gélineau
This exploratory study aims at answering the following research question: Are the h-index and some of its derivatives discriminatory when applied to rank social scientists with different epistemological beliefs and methodological preferences? This study reports the results of five Tobit and two negative binomial regression models taking as dependent variable the h-index and six of its derivatives, using a dataset combining bibliometric data collected with the PoP software with cross-sectional data of 321 Quebec social scientists in Anthropology, Sociology, Social Work, Political Science, Economics and Psychology. The results reveal an epistemological/methodological effect making positivists and quantitativists globally more productive than constructivists and qualitativists.
Scientific authorship has important implications in science since it reflects the contribution to research of the different individual scientists and it is considered by evaluation committees in research assessment processes. This study analyses the order of authorship in the scientific output of 1,064 permanent scientists at the Spanish CSIC (WoS, 1994–2004). The influence of age, professional rank and bibliometric profile of scientists over the position of their names in the byline of publications is explored in three different research areas: Biology and Biomedicine, Materials Science and Natural Resources. There is a strong trend for signatures of younger researchers and those in the lower professional ranks to appear in the first position (junior signing pattern), while more veteran or highly-ranked ones, who tend to play supervisory functions in research, are proportionally more likely to sign in the last position (senior signing pattern). Professional rank and age have an effect on authorship order in the three fields analysed, but there are inter-field differences. Authorship patterns are especially marked in the most collaboration-intensive field (i.e. Biology and Biomedicine), where professional rank seems to be more significant than age in determining the role of scientists in research as seen through their authorship patterns, while age has a more significant effect in the least collaboration-intensive field (Natural Resources).
Authors:Ludo Waltman, Nees Jan van Eck, Thed N. van Leeuwen, Martijn S. Visser, and Anthony F. J. van Raan
We present an empirical comparison between two normalization mechanisms for citation-based indicators of research performance. These mechanisms aim to normalize citation counts for the field and the year in which a publication was published. One mechanism is applied in the current so-called crown indicator of our institute. The other mechanism is applied in the new crown indicator that our institute is currently exploring. We find that at high aggregation levels, such as at the level of large research institutions or at the level of countries, the differences between the two mechanisms are very small. At lower aggregation levels, such as at the level of research groups or at the level of journals, the differences between the two mechanisms are somewhat larger. We pay special attention to the way in which recent publications are handled. These publications typically have very low citation counts and should therefore be handled with special care.
The h-index has received an enormous attention for being an indicator that measures the quality of researchers and organizations. We investigate to what degree authors can inflate their h-index through strategic self-citations with the help of a simulation. We extended Burrell's publication model with a procedure for placing self-citations, following three different strategies: random self-citation, recent self-citations and h-manipulating self-citations. The results show that authors can considerably inflate their h-index through self-citations. We propose the q-index as an indicator for how strategically an author has placed self-citations, and which serves as a tool to detect possible manipulation of the h-index. The results also show that the best strategy for an high h-index is publishing papers that are highly cited by others. The productivity has also a positive effect on the h-index.
Inventions combine technological features. When features are barely related, burdensomely broad knowledge is required to identify the situations that they share. When features are overly related, burdensomely broad knowledge is required to identify the situations that distinguish them. Thus, according to my first hypothesis, when features are moderately related, the costs of connecting and costs of synthesizing are cumulatively minimized, and the most useful inventions emerge. I also hypothesize that continued experimentation with a specific set of features is likely to lead to the discovery of decreasingly useful inventions; the earlier-identified connections reflect the more common consumer situations. Covering data from all industries, the empirical analysis provides broad support for the first hypothesis. Regressions to test the second hypothesis are inconclusive when examining industry types individually. Yet, this study represents an exploratory investigation, and future research should test refined hypotheses with more sophisticated data, such as that found in literature-based discovery research.
This study presents a historical overview of the International Conference on Human Robot Interaction (HRI). It summarizes its growth, internationalization and collaboration. Rankings for countries, organizations and authors are provided. Furthermore, an analysis of the military funding for HRI papers is performed. Approximately 20% of the papers are funded by the US Military. The proportion of papers from the US is around 65% and the dominant role of the US is only challenged by the strong position of Japan, in particular by the contributions by ATR.
This paper presents a methodology to aggregate multidimensional research output. Using a tailored version of the non-parametric
Data Envelopment Analysis model, we account for the large heterogeneity in research output and the individual researcher preferences
by endogenously weighting the various output dimensions. The approach offers three important advantages compared to the traditional
approaches: (1) flexibility in the aggregation of different research outputs into an overall evaluation score; (2) a reduction
of the impact of measurement errors and a-typical observations; and (3) a correction for the influences of a wide variety
of factors outside the evaluated researcher’s control. As a result, research evaluations are more effective representations
of actual research performance. The methodology is illustrated on a data set of all faculty members at a large polytechnic
university in Belgium. The sample includes questionnaire items on the motivation and perception of the researcher. This allows
us to explore whether motivation and background characteristics (such as age, gender, retention, etc.,) of the researchers
explain variations in measured research performance.
Authors:Reindert K. Buter, Ed. C. M. Noyons, and Anthony F. J. Van Raan
We define converging research as the emergence of an interdisciplinary research area from fields that did not show interdisciplinary connections before. This paper presents a process to search for converging research using journal subject categories as a proxy for fields and citations to measure interdisciplinary connections, as well as an application of this search. The search consists of two phases: a quantitative phase in which pairs of citing and cited fields are located that show a significant change in number of citations, followed by a qualitative phase in which thematic focus is sought in publications associated with located pairs. Applying this search on publications from the Web of Science published between 1995 and 2005, 38 candidate converging pairs were located, 27 of which showed thematic focus, and 20 also showed a similar focus in the other, reciprocal pair.
Collaboration between researchers and between research organizations is generally considered a desirable course of action,
in particular by some funding bodies. However, collaboration within a multidisciplinary community, such as the Computer–Human
Interaction (CHI) community, can be challenging. We performed a bibliometric analysis of the CHI conference proceedings to
determine if papers that have authors from different organization or countries receive more citations than papers that are
authored by members of the same organization. There was no significant difference between these three groups, indicating that
there is no advantage for collaboration in terms of citation frequency. Furthermore, we tested if papers written by authors
from different organizations or countries receive more best paper awards or at least award nominations. Papers from only one
organization received significantly fewer nominations than collaborative papers.
Authors:John Parker, Christopher Lortie, and Stefano Allesina
In science, a relatively small pool of researchers garners a disproportionally large number of citations. Still, very little
is known about the social characteristics of highly cited scientists. This is unfortunate as these researchers wield a disproportional
impact on their fields, and the study of highly cited scientists can enhance our understanding of the conditions which foster
highly cited work, the systematic social inequalities which exist in science, and scientific careers more generally. This
study provides information on this understudied subject by examining the social characteristics and opinions of the 0.1% most
cited environmental scientists and ecologists. Overall, the social characteristics of these researchers tend to reflect broader
patterns of inequality in the global scientific community. However, while the social characteristics of these researchers
mirror those of other scientific elites in important ways, they differ in others, revealing findings which are both novel
and surprising, perhaps indicating multiple pathways to becoming highly cited.