Usage Bibliometrics

Scholarly usage data provides unique opportunities to address the known shortcomings of citation analysis. However, the collection, processing and analysis of usage data remains an area of active research. This article provides a review of the state-of-the-art in usage-based informetric, i.e. the use of usage data to study the scholarly process.Comment: Publisher's PDF (by permission). Publisher web site: books.infotoday.com/asist/arist44.shtm

Quantifying the impact of weak, strong, and super ties in scientific careers

Scientists are frequently faced with the important decision to start or terminate a creative partnership. This process can be influenced by strategic motivations, as early career researchers are pursuers, whereas senior researchers are typically attractors, of new collaborative opportunities. Focusing on the longitudinal aspects of scientific collaboration, we analyzed 473 collaboration profiles using an ego-centric perspective which accounts for researcher-specific characteristics and provides insight into a range of topics, from career achievement and sustainability to team dynamics and efficiency. From more than 166,000 collaboration records, we quantify the frequency distributions of collaboration duration and tie-strength, showing that collaboration networks are dominated by weak ties characterized by high turnover rates. We use analytic extreme-value thresholds to identify a new class of indispensable `super ties', the strongest of which commonly exhibit >50% publication overlap with the central scientist. The prevalence of super ties suggests that they arise from career strategies based upon cost, risk, and reward sharing and complementary skill matching. We then use a combination of descriptive and panel regression methods to compare the subset of publications coauthored with a super tie to the subset without one, controlling for pertinent features such as career age, prestige, team size, and prior group experience. We find that super ties contribute to above-average productivity and a 17% citation increase per publication, thus identifying these partnerships - the analog of life partners - as a major factor in science career development.Comment: 13 pages, 5 figures, 1 Tabl

The "Names Game": Harnessing Inventors' Patent Data for Economic Research

The goal of this paper is to lay out a methodology and corresponding computer algorithms, that allow us to extract the detailed data on inventors contained in patents, and harness it for economic research. Patent data has long been used in empirical research in economics, and yet the information on the identity (i.e. the names and location) of the patents’ inventors has seldom been deployed in a large scale, primarily because of the “who is who” problem: the name of a given inventor may be spelled differently across her/his patents, and the exact same name may correspond to different inventors (i.e. the “John Smith” problem). Given that there are over 2 million patents with 2 inventors per patent on average, the “who is who” problem applies to over 4 million “records”, which is obviously too large to tackle manually. We have thus developed an elaborate methodology and computerized procedure to address this problem in a comprehensive way. The end result is a list of 1.6 million unique inventors from all over the world, with detailed data on their patenting histories, their employers, co-inventors, etc. Forty percent of them have more than one patent, and 70,000 have more than 10 patents. We can trace those multiple inventors across time and space, and thus study the causes and consequences of their mobility across countries, regions, and employers. Given the increasing availability of large computerized data sets on individuals, there may be plenty of opportunities to deploy this methodology to other areas of economic research as well.

Social Influence Given (Partially) Deliberate Matching: Career Imprints in the Creation of Academic Entrepreneurs

Actors often match with associates on a small set of dimensions that matter most for the particular relationship at hand. In so doing, they are exposed to unanticipated social influences because counterparts have more interests, attitudes, and preferences than would-be associates considered when they first chose to pair. This implies that some apparent social influences (those tied to the rationales for forming the relationship) are endogenous to the matching process, while others (those that are incidental to the formation of the relationship) may be conditionally exogenous, thus enabling causal estimation of peer effects. We illustrate this idea in a new dataset tracking the training and professional activities of academic biomedical scientists. In qualitative and quantitative analyses, we show that scientists match to their postdoctoral mentors based on two dominant factors, geography and scientific focus. They then adopt their advisers' orientations toward commercial science as evidenced by the transmission of patenting behavior, but they do not match on this dimension. We demonstrate this in two-stage models that adjust for the endogeneity of the matching process, using a modification of propensity score estimation and a sample selection correction with valid exclusion restrictions. Furthermore, we draw on qualitative accounts of the matching process recorded in oral histories of the career choices of the scientists in our data. All three methods-qualitative description, propensity score estimators, and those that tackle selection on unobservable factors-are potential approaches to establishing evidence of social influence in partially endogenous networks, and they may be especially persuasive in combination.

Social media metrics for new research evaluation

This chapter approaches, both from a theoretical and practical perspective, the most important principles and conceptual frameworks that can be considered in the application of social media metrics for scientific evaluation. We propose conceptually valid uses for social media metrics in research evaluation. The chapter discusses frameworks and uses of these metrics as well as principles and recommendations for the consideration and application of current (and potentially new) metrics in research evaluation.Comment: Forthcoming in Glanzel, W., Moed, H.F., Schmoch U., Thelwall, M. (2018). Springer Handbook of Science and Technology Indicators. Springe

Functional differentiation and grammatical competition in the English Jespersen Cycle

Wallage argues for a model of the Middle English Jespersen Cycle in which each of its diachronic stages are functionally equivalent competitors in the sense proposed by Kroch. However, recent work on the Jespersen Cycle in various Romance languages by Schwenter, Hansen and Hansen & Visconti has argued that the forms in competition during the Jespersen Cycle are not simply diachronic stages, but perform diUerent pragmatic or discourse functions. Hansen and Hansen & Visconti suggest that functional change may therefore underpin the Jespersen Cycle in these languages. Hence this paper explores the interface between pragmatic or functional change, and change in the syntax of sentential negation. Analysis of data from the PPPCME? (Kroch & Taylor) show that ne (stage one) and ne. . . not(stage two) are similarly functionally diUerentiated during the ME Jespersen Cycle: ne. . . not is favoured in propositions that are discourse-old (given, or recoverable from the preceding discourse), whereas ne is favoured in propositions that are discourse-new. Frequency data appear to show the loss of these constraints over time. However, I argue that these frequency data are not conclusive evidence for a shift in the functions of ne or ne. . . not. Indeed, the results of a regression analysis indicate that these discourse constraints remain constant throughout Middle English, in spite of the overall spread of ne. . . not as the Jespersen Cycle progresses. Therefore, I conclude the spread of ne. . . not is independent of these particular discourse constraints on its use, rather than the result of changes in, or loss of, these constraints