Mathematical Approaches to Modeling Science from an Algorithmic-Historiography Perspective

Lucio-Arias, Diana; Scharnhorst, Andrea

doi:10.1007/978-3-642-23068-4_2

Cited by 6 publications

(3 citation statements)

References 48 publications

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“…The intent of this article is to use an economic model of cooperative game theory to predict the level of social impact of scholarly papers created by specific citation networks. Lucio‐Arias and Scharnhorst () connect this proposal with the history of citation network analysis from a mathematical approach.…”

Section: Introductionmentioning

confidence: 99%

Social impact of scholarly articles in a citation network

García

Rodrı́guez-Sánchez

Fdez-Valdivia

2014

Asso for Info Science & Tech

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The intent of this article is to use cooperative game theory to predict the level of social impact of scholarly papers created by citation networks. Social impact of papers can be defined as the net effect of citations on a network. A publication exerts direct and indirect influence on others (e.g., by citing articles) and is itself influenced directly and indirectly (e.g., by cited articles). This network leads to an influence structure of citing and cited publications. Drawing on cooperative game theory, our research problem is to translate into mathematical equations the rules that govern the social impact of a paper in a citation network. In this article, we show that when citation relationships between academic papers function within a citation structure, the result is social impact instead of the (individual) citation impact of each paper. Mathematical equations explain the interaction between papers in such a citation structure. The equations show that the social impact of a paper is affected by the (individual) citation impact of citing publications, immediacy of citing articles, and number of both citing and cited papers. Examples are provided for several academic papers.

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Section: Introductionmentioning

confidence: 99%

Social impact of scholarly articles in a citation network

García

Rodrı́guez-Sánchez

Fdez-Valdivia

2014

Asso for Info Science & Tech

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“…Goffman's work showcases the complex relationship between mathematical, theoretical models and their empirical validation. Using his model, it is possible to define with which possibility a researcher becomes 'infected' with an idea and the predicted growth rate of a new scientific field can be compared with the actual growth rate (Wagner-Döbler, 1999), see review of follow-up studies in (Lucio-Arias & Scharnhorst, 2012)). Case studies also show that it is not easy to validate all processes inscribed in Goffman's model (Burger & Bujdoso, 1985).Goffman's model is only one out of many approaches to conceptualize science.…”

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Modeling the Structure and Dynamics of Science Using Books

Ginda,

Scharnhorst,

Börner

2016

Theories of Informetrics and Scholarly Communication

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Prize annually to scholars that have made a distinguished contribution to the field. The first three award recipients were Derek de Solla Price (1981), Robert K. , and Thomas S. Kuhn and their books Little Science, Big Science (Price, 1963), The Sociology of Science The Structure of Scientific Revolutions (Kuhn, 1962) are included in this analysis.Predictive models of science (computational and mathematical) are developed in scientometrics, bibliometrics, system dynamics, physics and mathematics, but also more recently in a new branch of philosophy of science and cognition (Payette, 2012). One of the first predictive models was introduced by Goffman-he used a model originally developed to predict the spread of diseases to describe the spreading of ideas (Goffman & Nevill 1964;Goffman 1966;Harmon 2008). The so-called SIR model orders researchers in three categories: the number researchers 'susceptible' to a new idea but not yet infected with it (S), the number of 'infected' researchers (I), and the number of 'recovered' researchers (R) who lost interest and will not return to the idea. The model presumes that boundaries of scientific fields and/or invisible colleges (Crane, 1972) can be defined. Goffman's work showcases the complex relationship between mathematical, theoretical models and their empirical validation. Using his model, it is possible to define with which possibility a researcher becomes 'infected' with an idea and the predicted growth rate of a new scientific field can be compared with the actual growth rate (Wagner-Döbler, 1999), see review of follow-up studies in (Lucio-Arias & Scharnhorst, 2012)). Case studies also show that it is not easy to validate all processes inscribed in Goffman's model (Burger & Bujdoso, 1985).Goffman's model is only one out of many approaches to conceptualize science. As of today, there exists no unifying framework that would interlink models-neither in terms of co-author communities nor in terms of citation linkages between publications. When (Lucio-Arias & Scharnhorst, 2012) presented a bibliometric study of a set of relevant LIS journals

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“…Historical overview of the occurrence of certain mathematical modelssource:Lucio-Arias and Scharnhorst (2012) …”

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confidence: 99%

Classification and Development of Mathematical Models and Simulation for Industrial Ecology

Schulze¹

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Recent publications call for a higher focus on implementation of the theoretical concept of industrial ecology. It embodies the idea that collaborating companies use each other's waste and byproducts following the example of the natural metabolism. Subject matter of this work is the practical application of this idea, i.e. eco-industrial parks and networks. In addition to the positive impact on the environment due to a reduction of pressure on limited natural resources, existing cases show that benefits can simultaneously be achieved for all three dimensions of sustainable development, including the economy and society. In order to promote this concept and thus facilitate the implementation of sustainable development in the private sector, this thesis proposes an Interactive Optimized Negotiation Algorithm (IONA) embedding a mixed-integer linear program with weighted achievement functions. This flexible network model supports the establishment of new industrial ecology in practice. It can flexibly be adapted to various circumstances and overcomes major critiques of existing approaches. In addition to the computer implementation of this advanced modeling approach, this work provides a catalogue of requirements to meet when modeling industrial ecology. The approach considers multiple objectives, different stakeholder interests, and various material flow types. The closing study of two cases shows the comprehensive capabilities of the program. Exceeding the scope of this work, the computer program can be used to conduct studies of existing networks regarding their stability when facing today's increasing necessity to set and meet environmental and social objectives. iii ACKNOWLEDGMENTS Foremost, I would like to express my sincere gratitude to my advisor Dr. Manbir Sodhi for the continuous support of my research, for his patience, motivation, enthusiasm, and immense knowledge. His guidance helped me in all the time of research and writing of this thesis. Besides my advisor, I thank Dr. David Taggart, Dr. Mercedes A. Rivero-Hudec, and Dr. Vinka Craver, for their encouragement and insightful comments. My sincere thanks also go to Prof. Dr. Thomas Spengler, who supported me over the long distance from Technische Universität Braunschweig, Germany and on location of my research with inspirational discussion and comments in both my professional career and personal life. A special acknowledgement goes to Rene Minnocci. Her dedicative support, encouragement, and effort in my personal life and for this thesis were an enduring source of energy and of great value to the outcome of this research project. You are an amazing person and important part of my life. Last but not the least, I would like to thank my whole family. I particularly thank, my parents Marion and Hans-Jürgen Schulze as well as my brother Marco Schulze for their constant support. Without their enduring love and care in every situation of my life I could not have gone this path and reached the point where I am today. I cherish every moment of my life thanks to y...

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Mathematical Approaches to Modeling Science from an Algorithmic-Historiography Perspective

Cited by 6 publications

References 48 publications

Social impact of scholarly articles in a citation network

Social impact of scholarly articles in a citation network

Modeling the Structure and Dynamics of Science Using Books

Classification and Development of Mathematical Models and Simulation for Industrial Ecology

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