{"product_id":"predicting-the-dynamics-of-research-impact-9783030866679","title":"Predicting the Dynamics of Research Impact","description":"\u003cp\u003e • Author(s): Yannis Manolopoulos\u003cbr\u003e • Publisher: Springer\u003cbr\u003e • Publisher Imprint: Springer\u003cbr\u003e • BISAC: System Administration - Storage \u0026amp; Retrieval\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFrom the Back Cover\u003c\/b\u003e\u003cbr\u003eThis book provides its readers with an introduction to interesting prediction and science dynamics problems in the field of Science of Science. Prediction\u003ci\u003e \u003c\/i\u003efocuses 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.\u003c\/p\u003e\u003cp\u003eThe 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. \u003c\/p\u003e 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.","brand":"Springer","offers":[{"title":"Hardcover","offer_id":45279492964503,"sku":"9783030866679","price":12486.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9783030866679.webp?v=1769293729","url":"https:\/\/atlanticbooks.com\/products\/predicting-the-dynamics-of-research-impact-9783030866679","provider":"Atlantic Books","version":"1.0","type":"link"}