Frontiers in Research Metrics and Analytics 

About: Frontiers in Research Metrics and Analytics is an academic journal published by Frontiers Media. The journal publishes majorly in the area(s): Medicine & Computer science. It has an ISSN identifier of 2504-0537. It is also open access. Over the lifetime, 297 publications have been published receiving 1829 citations. The journal is also known as: RMA & Research metrics and analytics.

Dimensions: Building Context for Search and Evaluation

Abstract: Dimensions is a new database that focussed on a different set of problems to other scholarly search systems. Specifically, by the including not only data about publications and their natural associated citation graph, but by also including awarded grant data, patent data and clinical data and altmetric attention data, Dimensions holds a representation of an n-partite graph associated with the heterogeneous research objects. These objects have been treated as heterogeneous, but need to be brought onto the same footing (and homogenised) in order that they should make sense to a user. The links (or edges) in the expanded network of objects is created through extensive use of text mining and machine learning to extract and to normalise data. This article gives an overview of the techniques used to create the Dimensions dataset.

Citations: Indicators of Quality? The Impact Fallacy

Abstract: We argue that citation is a composed indicator: short-term citations can be considered as currency at the research front, whereas long-term citations can contribute to the codification of knowledge claims into concept symbols. Knowledge claims at the research front are more likely to be transitory and are therefore problematic as indicators of quality. Citation impact studies focus on short-term citation, and therefore tend to measure not epistemic quality, but involvement in current discourses in which contributions are positioned by referencing. We explore this argument using three case studies: (1) citations of the journal Soziale Welt as an example of a venue that tends not to publish papers at a research front, unlike, for example, JACS; (2) Robert Merton as a concept symbol across theories of citation; and (3) the Multi-RPYS (“Multi-Referenced Publication Year Spectroscopy”) of the journals Scientometrics, Gene, and Soziale Welt. We show empirically that the measurement of “quality” in terms of citations can further be qualified: short-term citation currency at the research front can be distinguished from longer-term processes of incorporation and codification of knowledge claims into bodies of knowledge. The recently introduced Multi-RPYS can be used to distinguish between short-term and long-term impacts.

A Glimpse of the First Eight Months of the COVID-19 Literature on Microsoft Academic Graph: Themes, Citation Contexts, and Uncertainties

Abstract: As scientists worldwide search for answers to the overwhelmingly unknown behind the deadly pandemic, the literature concerning COVID-19 has been growing exponentially. Keeping abreast of the body of literature at such a rapidly advancing pace poses significant challenges not only to active researchers but also to society as a whole. Although numerous data resources have been made openly available, the analytic and synthetic process that is essential in effectively navigating through the vast amount of information with heightened levels of uncertainty remains a significant bottleneck. We introduce a generic method that facilitates the data collection and sense-making process when dealing with a rapidly growing landscape of a research domain such as COVID-19 at multiple levels of granularity. The method integrates the analysis of structural and temporal patterns in scholarly publications with the delineation of thematic concentrations and the types of uncertainties that may offer additional insights into the complexity of the unknown. We demonstrate the application of the method in a study of the COVID-19 literature.

Reliability of Google Trends: Analysis of the Limits and Potential of Web Infoveillance During COVID-19 Pandemic and for Future Research

Abstract: Background: Alongside the COVID-19 pandemic, government authorities around the world have had to face a growing infodemic capable of causing serious damages to public health and economy In this context, the use of infoveillance tools has become a primary necessity Objective: The aim of this study is to test the reliability of a widely used infoveillance tool which is Google Trends In particular, the paper focuses on the analysis of relative search volumes (RSVs) quantifying their dependence on the day they are collected Methods: RSVs of the query coronavirus + covid during February 1-December 4, 2020 (period 1), and February 20-May 18, 2020 (period 2), were collected daily by Google Trends from December 8 to 27, 2020 The survey covered Italian regions and cities, and countries and cities worldwide The search category was set to all categories Each dataset was analyzed to observe any dependencies of RSVs from the day they were gathered To do this, by calling i the country, region, or city under investigation and j the day its RSV was collected, a Gaussian distribution X i = X ( σ i , x ¯ i ) was used to represent the trend of daily variations of x i j = R S V s i j When a missing value was revealed (anomaly), the affected country, region or city was excluded from the analysis When the anomalies exceeded 20% of the sample size, the whole sample was excluded from the statistical analysis Pearson and Spearman correlations between RSVs and the number of COVID-19 cases were calculated day by day thus to highlight any variations related to the day RSVs were collected Welch's t-test was used to assess the statistical significance of the differences between the average RSVs of the various countries, regions, or cities of a given dataset Two RSVs were considered statistical confident when t 15 A dataset was deemed unreliable if the confident data exceeded 20% (confidence threshold) The percentage increase Δ was used to quantify the difference between two values Results: Google Trends has been subject to an acceptable quantity of anomalies only as regards the RSVs of Italian regions (0% in both periods 1 and 2) and countries worldwide (97% during period 1 and 109% during period 2) However, the correlations between RSVs and COVID-19 cases underwent significant variations even in these two datasets ( M a x | Δ | = + 625 % for Italian regions, and M a x | Δ | = + 175 % for countries worldwide) Furthermore, only RSVs of countries worldwide did not exceed confidence threshold Finally, the large amount of anomalies registered in Italian and international cities' RSVs made these datasets unusable for any kind of statistical inference Conclusion: In the considered timespans, Google Trends has proved to be reliable only for surveys concerning RSVs of countries worldwide Since RSVs values showed a high dependence on the day they were gathered, it is essential for future research that the authors collect queries' data for several consecutive days and work with their RSVs averages instead of daily RSVs, trying to minimize the standard errors until an established confidence threshold is respected Further research is needed to evaluate the effectiveness of this method

A Global Comparison of Scientific Mobility and Collaboration According to National Scientific Capacities

Abstract: This study compares the flows of mobile researchers and the number of publications in international collaboration within the context of scientific and economic capacities. The goal is to identify the convergence or discrepancy of countries in mobility and collaboration and determine the positions and relative influence of countries in both processes. Using affiliation data from scientific publications, we analyze the distributions and networks of collaboration and mobility and their structural differences. The results show that there is a significant relationship between the flow of mobile researchers and the capacity for publishing with foreign partners in the more prolific countries, although mobility is always lower than collaboration. Size matters and scientific relationship are highly resource-dependent. The Advanced and Proficient countries accumulate the highest proportion of the mobile authors and international publications with an extremely low representation of mobility in Developing and Lagging countries. In addition, the placement of countries is not always consistent in both networks, revealing the distinct roles, with particular instability for lower income countries. The more resources available in a country (both scientific and economic) the greater the likelihood of attracting foreign partners and mobilizing human capital. The policy relevance of these structural differences are described and a brief description of the limitations and future research are provided.