Becoming Metric Wise

Becoming Metric-Wise: A Bibliometric Guide for Researchers aims to inform researchers about metrics so that they become aware of the evaluative techniques being applied to their scientific output. Understanding these concepts will help them during their funding initiatives, and in hiring and tenure. The book not only describes what indicators do (or are designed to do, which is not always the same thing), but also gives precise mathematical formulae so that indicators can be properly understood and evaluated. Metrics have become a critical issue in science, with widespread international discussion taking place on the subject across scientific journals and organizations. As researchers should know the publication-citation context, the mathematical formulae of indicators being used by evaluating committees and their consequences, and how such indicators might be misused, this book provides an ideal tome on the topic. Provides researchers with a detailed understanding of bibliometric indicators and their applications Empowers researchers looking to understand the indicators relevant to their work and careers Presents an informed and rounded picture of bibliometrics, including the strengths and shortcomings of particular indicators Supplies the mathematics behind bibliometric indicators so they can be properly understood Written by authors with longstanding expertise who are considered global leaders in the field of bibliometrics

New digital technologies have transformed how scientific information is created, disseminated—and discovered. The emergence of new forms of scientific publishing based on open science and open access have caused a major shift in scientific communication and a restructuring of the flow of information. Specialized indexing services and search engines are trying to get into information seekers’ minds to understand what users are actually looking for when typing all these keywords or drawing chemical structures. Using artificial intelligence (AI), machine learning, and semantic indexing, these "discovery agents" are trying to anticipate users’ information needs. In this highly competitive environment, authors should not sit and rely only on publishers, search engines, and indexing services to make their works visible. They need to communicate about their research and reach out to a larger audience. Driving Science Information Discovery in the Digital Age looks through the "eyes" of the main "players" in this "game" and examines the discovery of scientific information from three different, but intertwined, perspectives: Discovering, managing, and using information (Information seeker perspective) Publishing, disseminating, and making information discoverable (Publisher perspective) Creating, spreading, and promoting information (Author perspective). Presents an overview of the current scientific publishing landscape Shows how users can search for scientific information more efficiently Critically analyses the metrics used to measure the quality of journals and the impact of research Looks at the discovery of scientific information from the perspectives of information seekers, publishers, and authors Delves into the practices used by specialized indexing services and search engines to process scientific information and make it discoverable Recommends strategies that authors could use to promote their research

"Bibliometrics and altmetrics are increasingly becoming the focus of interest in the context of research evaluation. The Handbook Bibliometrics provides a comprehensive introduction to quantifying scientific output in addition to a historical derivation, individual indicators, institutions, application perspectives and data bases. Furthermore, application scenarios, training and qualification on bibliometrics and their implications are considered"--Publisher's website.

This book provides its readers with an introduction to interesting prediction and science dynamics problems in the field of Science of Science. Prediction focuses on the forecasting of future performance (or impact) of an entity, either a research article or a scientist, and also the prediction of future links in collaboration networks or identifying missing links in citation networks. The single chapters are written in a way that help the reader gain a detailed technical understanding of the corresponding subjects, the strength and weaknesses of the state-of-the-art approaches for each described problem, and the currently open challenges. While chapter 1 provides a useful contribution in the theoretical foundations of the fields of scientometrics and science of science, chapters 2-4 turn the focal point to the study of factors that affect research impact and its dynamics. Chapters 5-7 then focus on article-level measures that quantify the current and future impact of scientific articles. Next, chapters 8-10 investigate subjects relevant to predicting the future impact of individual researchers. Finally, chapters 11-13 focus on science evolution and dynamics, leveraging heterogeneous and interconnected data, where the analysis of research topic trends and their evolution has always played a key role in impact prediction approaches and quantitative analyses in the field of bibliometrics. Each chapter can be read independently, since it includes a detailed description of the problem being investigated along with a thorough discussion and study of the respective state-of-the-art. Due to the cross-disciplinary character of the Science of Science field, the book may be useful to interested readers from a variety of disciplines like information science, information retrieval, network science, informetrics, scientometrics, and machine learning, to name a few. The profiles of the readers may also be diverse ranging from researchers and professors in the respective fields to students and developers being curious about the covered subjects.

Scientometrics for the Humanities and Social Sciences is the first ever book on scientometrics that deals with the historical development of both quantitative and qualitative data analysis in scientometric studies. It focuses on its applicability in new and emerging areas of inquiry. This important book presents the inherent potential for data mining and analysis of qualitative data in scientometrics. The author provides select cases of scientometric studies in the humanities and social sciences, explaining their research objectives, sources of data and methodologies. It illustrates how data can be gathered not only from prominent online databases and repositories, but also from journals that are not stored in these databases. With the support of specific examples, the book shows how data on demographic variables can be collected to supplement scientometric data. The book deals with a research methodology which has an increasing applicability not only to the study of science, but also to the study of the disciplines in the humanities and social sciences.

Productivity and Publishing: Writing Processes for New Scholars & Researchers by Margaret-Mary Sulentic Dowell, Leah Katherine Saal, Cynthia F. DiCarlo, and Tynisha D. Willingham takes the challenges and confusion out of academic writing and journal publishing by empowering readers to find the writing process that works for them. Activities and writing exercises help readers determine their research agendas, set realistic writing goals, , and follow time-tested and editor-approved processes for writing and revising journal articles. Topics cover the writing and publishing process from start to finish, addressing common issues for new academics like avoiding the blank page, selecting an appropriate journal, dealing with reviews, and leveraging your research into multiple articles and a comprehensive research agenda. Experts weigh in on crucial topics such as scholarly metrics and exposure and offer a journal editor’s perspective on the writing and publishing process. Build your academic career on a solid foundation with Productivity and Publishing.

This volume presents a selection of peer-reviewed papers that address the latest developments in the methodology and applications of data analysis and classification tools to micro- and macroeconomic problems. The contributions were originally presented at the 30th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2021, held online in Poznań, Poland, September 8–10, 2021. Providing a balance between methodological and empirical studies, and covering a wide range of topics, the book is divided into five parts focusing on methods and applications in finance, economics, social issues and to COVID-19 data. The book is aimed at a wide audience, including researchers at universities and research institutions, PhD students, as well as practitioners, data scientists and employees in public statistical institutions.

This book probes the dynamics of academic research and scholarship evaluation. Readers will learn about scholarly metric evolution, impact factors, disruptive technologies, and a myriad of forces affecting policy development at institutions through an examination of widely-used measurements and growing concerns about their influence.