diff --git a/entries/mturk_workers/__init__.py b/entries/mturk_workers/__init__.py
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+++ b/entries/mturk_workers/__init__.py
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+#! /usr/bin/env python
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2020-2026 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 Affero 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 Affero General Public License for more
+# details.
+#
+# You should have received a copy of the GNU Affero General Public License along
+# with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+from .. import *
+
+title = "Amazon Mechanical Turk worker communication network (2015)"
+description = """The communication network among workers of Amazon Mechanical Turk (MTurk), an online crowdsourcing labor market, mapped by Yin et al. Workers were recruited with a task posted on MTurk in August and September 2015, open to all workers, which was completed by 10,354 workers (approximately a census of the active workers at the time). Each worker created an anonymous nickname, and then self-reported the other workers with whom they communicate (for instance through online forums dedicated to MTurk, or one-on-one channels such as e-mail, text messages or social media), by searching for their nicknames; workers could keep adding or removing edges after completing the task, and the network corresponds to the data collected on September 13, 2015. Each node is a worker, and an undirected edge connects two workers if one of them reported communicating with the other. Most workers (86.6%) did not report any connection and are isolated nodes. The worker attributes analyzed in the paper (country, forum use, etc.) are not included in the public data."""
+tags = ['Social', 'Online', 'Communication', 'Unweighted']
+url = 'https://mingyin.org/'
+citation = [('M. Yin, M. L. Gray, S. Suri, J. W. Vaughan, "The Communication Network Within the Crowd." Proceedings of the 25th International Conference on World Wide Web (WWW), 1293-1303 (2016)', 'https://doi.org/10.1145/2872427.2883036')]
+icon_hash = '5bec2723a7970b9d73465c37'
+upstream_license = None
+upstream_prefix = 'https://mingyin.org/data'
+files = [('turkernetwork_public.zip:turkernetwork_public/turker_network.csv', None, None)]
+
+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
+        with open_upstream_file(name, fnames, "r") as f:
+            # Header "From,To"; workers are numbered 1 to 10354
+            edges = numpy.loadtxt(f, dtype="int64", delimiter=",", skiprows=1,
+                                  ndmin=2)
+        g = Graph(directed=False)
+        g.add_vertex(10354)
+        g.add_edge_list(edges - 1)
+        yield alt, g