An analysis of the abstracts presented at the annual meetings of the Society for Neuroscience from 2001 to 2006

• Published in: PloS one Vol. 3; no. 4; p. e2052
• Main Authors: Lin, John M, Bohland, Jason W, Andrews, Peter, Burns, Gully A P C, Allen, Cara B, Mitra, Partha P
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 30.04.2008; Public Library of Science (PLoS)
• Subjects: Abstracting and Indexing as Topic - statistics & numerical data; Algorithms; Analysis; Artificial intelligence; Authorship; Bibliometrics; Cluster Analysis; Clustering; Communities; Community structure; Computational Biology; Computational Biology/Computational Neuroscience; Computational Biology/Literature Analysis; Computer Science; Computer Science/Applications; Computer Science/Information Technology; Congresses as Topic; Data analysis; Data mining; Data processing; Demographics; Demography; Dictionaries; Funding; Geography; Information management; Knowledge; Laboratories; Linguistics; Mathematics/Algorithms; Mathematics/Statistics; Meetings; Melanoma; National Institutes of Health (U.S.); Natural language processing; Nervous system; Neurodegenerative diseases; Neuroscience; Neurosciences; Research Support as Topic; Researchers; Science Policy; Search engines; Shrinkage; Societies, Medical; Society; Texts; United States; New York
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0002052

Annual meeting abstracts published by scientific societies often contain rich arrays of information that can be computationally mined and distilled to elucidate the state and dynamics of the subject field. We extracted and processed abstract data from the Society for Neuroscience (SFN) annual meeting abstracts during the period 2001-2006 in order to gain an objective view of contemporary neuroscience. An important first step in the process was the application of data cleaning and disambiguation methods to construct a unified database, since the data were too noisy to be of full utility in the raw form initially available. Using natural language processing, text mining, and other data analysis techniques, we then examined the demographics and structure of the scientific collaboration network, the dynamics of the field over time, major research trends, and the structure of the sources of research funding. Some interesting findings include a high geographical concentration of neuroscience research in the north eastern United States, a surprisingly large transient population (66% of the authors appear in only one out of the six studied years), the central role played by the study of neurodegenerative disorders in the neuroscience community, and an apparent growth of behavioral/systems neuroscience with a corresponding shrinkage of cellular/molecular neuroscience over the six year period. The results from this work will prove useful for scientists, policy makers, and funding agencies seeking to gain a complete and unbiased picture of the community structure and body of knowledge encapsulated by a specific scientific domain.