TY - CHAP
T1 - Citation networks
AU - Radicchi, Filippo
AU - Fortunato, Santo
AU - Vespignani, Alessandro
PY - 2012
Y1 - 2012
N2 - Bibliographic databases contain a huge amount of information on the dissemination of scientific knowledge and the relationships between papers, authors, and scientific work. Large-scale citation networks can be generated from these databases in order to provide a systems-level perspective on the processes at the root of the spreading of ideas, theories, and results in science. Citation networks are therefore one of the main proxies for our understanding of knowledge dynamics as well as invaluable systems for the quantitative analysis of the impact of specific scientific contributions, the emergence of technical and scientific areas, and the ranking of journals, institutions, and scientists. This chapter reviews recent developments made in the study of citation networks, ranging from empirical analyses of real systems and mathematical models of them, to the study of dynamic processes taking place in them and their potential applications. Furthermore, studying citation datasets with the tools of network theory opens new avenues towards a quantitative understanding of the dynamics of popularity with respect to papers, journals, and scientists, possibly leading to novel measures of impact and ranking.
AB - Bibliographic databases contain a huge amount of information on the dissemination of scientific knowledge and the relationships between papers, authors, and scientific work. Large-scale citation networks can be generated from these databases in order to provide a systems-level perspective on the processes at the root of the spreading of ideas, theories, and results in science. Citation networks are therefore one of the main proxies for our understanding of knowledge dynamics as well as invaluable systems for the quantitative analysis of the impact of specific scientific contributions, the emergence of technical and scientific areas, and the ranking of journals, institutions, and scientists. This chapter reviews recent developments made in the study of citation networks, ranging from empirical analyses of real systems and mathematical models of them, to the study of dynamic processes taking place in them and their potential applications. Furthermore, studying citation datasets with the tools of network theory opens new avenues towards a quantitative understanding of the dynamics of popularity with respect to papers, journals, and scientists, possibly leading to novel measures of impact and ranking.
UR - http://www.scopus.com/inward/record.url?scp=84858780514&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-23068-4_7
DO - 10.1007/978-3-642-23068-4_7
M3 - Chapter
AN - SCOPUS:84858780514
SN - 9783642230677
T3 - Understanding Complex Systems
SP - 233
EP - 257
BT - Models of Science Dynamics
ER -