"journals" ########## * list of full and abbreviated names of journals used for downloads from Web of Science ** journals.csv "data cleaning" ############### * list of identified reference strings ** ref.sou.csv * code for reference identification (by Felix Mattes) ** identify.references-revised.R "network" ######### * bipartite network of ** top-300 highly cited sources ** 6,494 papers in IR journals and books 2011-2015 citing at least two top-300 sources * data.frame sel.sou of selected top-300 sources (ordered by sou.id) ** columns: [1] sou.id = source id [2] fam.aut.1 = family name of first author [3] n.cit = number of citations 2006-2015 in expanded data set [4] year = year of first publication [5] ref = typical reference [6] co.aut = co-authors [7] title = title [8] journal = journal (of journal papers) [9] journal.abbr= abbreviation of journal [10] IR = classified as IR [11] v = volume [12] p = first page [13] sn.aut.1 = surname of first author [14] c.rank = citation rank of n.cit [15] r.n.cit = reduced number of citations (reduced to IR journals and books) [16] r.c.rank = citation rank of r.n.cit (ties broken by year) ** sel.sou-v12.RObj * number of ** nodes: n = 6,494 + 300 ** links: m = 30,835 * link list lili of citation links 2011-2015 from 6,494 papers to top-300 sources (and reverse) ** ids of cited sources: 1:300 in order of sel.sou ** ids of citing papers: 300 + 1:6494 ** columns: [1] n.1 = node 1 (id of citing paper in first m rows and of cited top-300 source in last m rows) [2] n.2 = node 2 (vice versa) ** lili.2011-2015-v2.300.RObj "Ward clusters of views" ######################## * made by Michael Heinz * used as seeds for link clustering ** cv.RObj "PsiMinL" ######### * R-package for memetic link clustering programmed by Andreas Prescher ** will be delivered by request * parameters of experiments in IR studies in R-scripts: ** adapt-Ward-seed-v5.R ** graph-v2.R ** run-phases-v4.R ** parameters-v2.R "link clusters" ############### * logical matrix v.Ls of 19 valid link clusters and m links ** names of 19 columns = names of clusters (cf. paper) ** names of m rows = number of links (parallel to lili[1:m,]) ** v.Ls-v6.RObj * numerical matrix ccs of cluster citations of top-300 sources ** contains internal degree of each top-300 source in each valid cluster and in the whole network (all) ** names of 21 columns = names of clusters (cf. paper) + all + IR (classication as in sel.sou) ** names of 300 rows = family name of first author and year of first publication (parallel to sel.sou) ** ccs-v7.RObj * R-code for getting ** full-member sources of a link cluster lc: which(ccs[,lc]==ccs[,"all"]) ** sources of a link cluster lc with membership grade larger than mg < 1: which(ccs[,lc] > mg * ccs[,"all"]) ** citation rank-list of sources with regard to internal degree in cluster lc rev(sort(ccs[ccs[,lc] > 0, lc]))

Data are described in the file read.me.R and in the paper "Topics as Clusters of Citation Links to Highly Cited Sources: The Case of Research on International Relations" by Frank Havemann. It will be available in arXiv. This work is part of the Global Pathways project (http://t1p.de/globalpathways) sponsored by DFG (grant RI 798/11-1). The raw data were obtained from the Web of Science database produced by Clarivate Analytics. Due to license restrictions, the data cannot be made openly available. To obtain Web of Science data, please contact Clarivate Analytics (https://clarivate.com/ products/web-of-science).

{"references": ["Frank Havemann (2020), Topics as Clusters of Citation Links to Highly Cited Sources: The Case of Research on International Relations"]}