Information networks in the directories APS and news have been used
to obtain the results presented in "Optimal timescale for community
detection in growing networks" (New Journal of Physics, 2019; also
available at https://arxiv.org/abs/1809.04943). The data have been
prepared by Matus Medo (matus.medo@unifr.ch).

The data can be used for research. Please acknowledge the original
article (see above) in all publications resulting from the use of
the data set. Do not redistribute the data without this README file.


=== APS citation networks ===
We use the APS citation data that were obtained on our request from
https://journals.aps.org/datasets. Our dataset contains all papers
published by the APS from 1893 until December 2013 and the links among
them. Importantly, paper metadata contains paper PACS codes which
allow us to construct subsets of the original dataset in a controlled
way (see https://journals.aps.org/PACS for details on the Physics and
Astronomy Classification Scheme, PACS). The original data comprise
539,974 papers and 5,992,897 citations among them. Majority of the
papers have some PACS codes assigned (404,999 out of 539,974; most of
the papers without PACS codes were published before 1977 when the PACS
classification scheme was introduced). The PACS codes have a three-
level hierarchy (for example, code "89.75.-k" represents "Complex
systems"). To construct subsets, we use the two top levels (for
example, "89.75.*") which results in larger subsets than when complete
PACS codes are used. Every paper that has a given two-level PACS code
is considered as part of the subset. For each subset, self-loops and
nodes that do not belong in the giant component are discarded. To
create the subsets, we chose two-level PACS codes whose aging speed
N/\tau_S covers a broad range of values. Only subsets with at least
1000 edges are used for further analysis (there are 27 of them). For
each network, we provide the link lists where the time information (in
days) is available for each citing-cited pair.


=== News citation networks ===
The news citation dataset was used to analyze the backbone of the
citation network and its impact on network centrality metrics (Spitz
and Gertz, Breaking the news: Extracting the sparse citation network
backbone of online news articles, Proceedings of the 2015 IEEE/ACM
International Conference on Advances in Social Networks Analysis and
Mining, 2015). The dataset consists of news published by various
outlets (newspapers and televisions) and citations among them. Since
most citations are among the news published by the same outlet (91\%),
we treat articles published by individual outlets as independent
datasets. For each subset, self-loops and nodes that do not belong in
the giant component are discarded. Only subsets with 500 edges or more
are included in the further analysis (there are 22 of them). For each
network, we provide the link lists and separate node lists with time
information for each node (columns when and, at a lower resolution,
date_only).


