__init__.py 2.27 KB
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#! /usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (C) 2020 Tiago de Paula Peixoto <tiago@skewed.de>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.

from .. import *

title = "Academica.edu (2011)"
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description = """Snapshot of the follower relationships among users of academia.edu, a platform for academics to share research papers, scraped in 2011. Nodes are users and a directed edge (i,j) denotes that user i follows j.[^icon]
[^icon]: Description obtained from the [ICON](https://icon.colorado.edu) project."""
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tags = ['Social', 'Online', 'Unweighted']
url = 'https://homes.cs.washington.edu/~fire/#section3'
citation = [('M. Fire et al. "Computationally Efficient Link Prediction in a Variety of Social Networks." ACM Transactions on Intelligent Systems and Technology 5(1), Article 10 (2013)', 'https://homes.cs.washington.edu/~fire/pdf/link_tists.pdf')]
icon_hash = '59fe94ceee01e9ab21ac7fc6'
ustream_license = None
upstream_prefix = 'https://www.ise.bgu.ac.il/faculty/fire/datasets'
files = [('academiaAnonymized.zip:academiaAnonymized/academia2Anonymized.csv', None, 'csv')]

def fetch_upstream(force=False):
    return fetch_upstream_files(__name__.split(".")[-1], upstream_prefix, files,
                                force)

@cache_network()
@coerce_props()
@annotate()
def parse(alts=None):
    global files
    name = __name__.split(".")[-1]
    for fnames, alt, fmt in files:
        if alts is not None and alt not in alts:
            continue
        if isinstance(fnames, str):
            fnames = [fnames]
        with ExitStack() as stack:
            fs = [stack.enter_context(open_upstream_file(name, fn, "rb")) for fn in fnames]
            g = parse_graph(fs, fmt, directed=True)
        yield alt, g