The analysis of scientific disciplines and their development using a Social Network Analysis Tool

Inhalt

1 Abstract

2 Table of figures

3 Introduction

4 Related Research

5 Theoretical Background
5.1 Social Network Analysis
5.1.1 General approach
5.1.2 Project appliance
5.2 Data source and concepts
5.2.1 Database: ISIWeb of Science
5.2.2 The concept of RFID
5.2.3 Additional concepts
5.3 Analysis-Tool: TeCFlow

6 Hypotheses
6.1 Hypothesis I: Key Journals for RFID
6.2 Hypothesis II: Diffusion over time

7 Analysis and Evaluation
7.1 Analysis on hypothesis I
7.2 Analysis on hypothesis II

8 Summary & Conclusion
8.1 Summary on Analysis
8.2 Further steps and research

9 Table of references A

1 Abstract

Journal databases provide an easy access to most scientifically relevant topics and articles. Since articles refer to other articles these, do provide a social network-like structure. Social networks follow certain patterns that contain relevant data about the current state or the development in the future. With these indications, we will try to use a social network Analysis tool in order to find such patterns within the field of sciences extracted from a scientific database. The tool we will be using is called TecFlow. The database is a partial extraction from ISIWeb.

Within this paper, two hypotheses are analysed and described. The focus lies on the centrality and importance of the concept of RFID over time.

Due to the actual relevance of social network analysis and new character of this paper, the analysis-results can lead to various future researches and studies, which are identified and described within this article.

2 Table of figures

Image 1: Roles within a network depending on Contribution Index and frequency 10

Image 2: Total Network for RFID 12

Image 3: Core Network on RFID (Communication Frequency > 10) 13

Image 4: Journal Heritage 14

Image 5: Number of published articles from 1993 to 2005 on the topic „RFID“ 15

Image 6: Dynamic view of the years 1993 and 1999 (with history) 15

Image 7: Dynamic view of the later years 2004 and 2005 where the boom occured on RFID (with history) 16

3 Introduction

Based on an international project between the Massachusetts Institute of Technology (MIT, USA), the Helsinki University of Technology (HUT, FIN) and the University of Cologne (UoC, GER), this paper describes the social network analysis of an scientific journal-platform called ISIweb.

Within the project, a group of students made a profund analysis on the “ISIWeb Web of Science” database, which is owned by Thomson Scientific. The focus lay on the analysis of Social Networks, and the identification of trends and communities within this network of academic papers. The analysis itself was conducted with the TeCFlow-tool for social network analysis, developed by the CKN project. Within the project, the student group analysed the social network for the concepts “RFID” and “Knowledge Work” and their importance and networks within ISIWeb. Based on these concepts, various hypotheses were dissected.

The paper describes the analysis and results for two of the main hypotheses for the concept of “RFID”. After depicting the theoretical background of social network analysis, a short description on RFID, TeCFlow and the understanding of social networks within an academic paper network like ISIWeb, the two hypotheses will be introduced.

The central part of the paper shows the analysis, conducted on the hypotheses and the research-results and findings. In the last chapter, some assumptions for further research-ideas are also given.

The goal of the paper is to give a short overview about the research, conducted within the international project and to describe possible research-opportunities on this subject in the future.

4. Related Research

During the last year, a few interesting articles were published about the topic. McGovern, Friedland et.al published a paper about the “Exploiting Relational Structure to Understand Publication Patterns in High-Energy Physics”^[1]. In their work, the authors analysed the citation network within the community for theoretical high-energy physics. Based on the arXiv.org- e-Print archive for physical papers and journals, the group analysed the citations practices between the various articles.

Similar to the approach, made in this paper, McGovern and Friedland made an empirical analysis based on a mathematical graph. One of the hypothesis, they tested was, that an article receives citations in two peaks. The first peak after submitting the article to the community. The second peak after sending it to arXiv. Within the empirical analysis, the hypothesis was tested and demonstrated.

Nerur, Sikora, et al developed another interesting empirical study about “Assessing the Relative Influence of Journals in A Citation Network”^[2]. They analysed the most important journals within the information technology-community, their roles and the relative influence of these journals by diving them into the groups of knowledge stores and key sources. Knowledge stores are journals, who cite other journals.

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^[1] MCGOVERN (Relational Structure)

^[2] NERUR (Relative Influence)