<?xml version='1.0' encoding='UTF-8'?><codeBook xmlns="ddi:codebook:2_5" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="ddi:codebook:2_5 https://ddialliance.org/Specification/DDI-Codebook/2.5/XMLSchema/codebook.xsd" version="2.5"><docDscr><citation><titlStmt><titl>Replication Data for: Right and left, partisanship predicts vulnerability to misinformation</titl><IDNo agency="DOI">doi:10.7910/DVN/6CZHH5</IDNo></titlStmt><distStmt><distrbtr source="archive">Harvard Dataverse</distrbtr><distDate>2020-10-07</distDate></distStmt><verStmt source="archive"><version date="2021-08-12" type="RELEASED">2</version></verStmt><biblCit>Dimitar Nikolov; Alessandro Flammini; Filippo Menczer, 2020, "Replication Data for: Right and left, partisanship predicts vulnerability to misinformation", https://doi.org/10.7910/DVN/6CZHH5, Harvard Dataverse, V2, UNF:6:Avb9rregQyEFA8q65GDGWA== [fileUNF]</biblCit></citation></docDscr><stdyDscr><citation><titlStmt><titl>Replication Data for: Right and left, partisanship predicts vulnerability to misinformation</titl><IDNo agency="DOI">doi:10.7910/DVN/6CZHH5</IDNo></titlStmt><rspStmt><AuthEnty affiliation="Indiana University">Dimitar Nikolov</AuthEnty><AuthEnty affiliation="Indiana University">Alessandro Flammini</AuthEnty><AuthEnty affiliation="Indiana University">Filippo Menczer</AuthEnty></rspStmt><prodStmt/><distStmt><distrbtr source="archive">Harvard Dataverse</distrbtr><contact affiliation="Indiana University" email="dimitar.g.nikolov@gmail.com">Nikolov, Dimitar</contact><depositr>Nikolov, Dimitar</depositr><depDate>2021-01-11</depDate></distStmt><holdings URI="https://doi.org/10.7910/DVN/6CZHH5"/></citation><stdyInfo><subject><keyword xml:lang="en">Computer and Information Science</keyword><keyword xml:lang="en">Social Sciences</keyword><keyword>Misinformation</keyword><keyword>Echo Chambers</keyword><keyword>Bias</keyword><keyword>Polarization</keyword></subject><abstract date="2021-01-11">&lt;p>The dataset consists of two files:&lt;/p>

&lt;p>1. &lt;em>anonymized_shares.json&lt;/em>: A collection of sharing actions, each  corresponding to a tweet posted in June 2017 in which one or more URLs were shared. The format is as follows:&lt;/p>

&lt;p>
&lt;pre>
{
    uid1: [
        {"domains": ["domain1", "domain2"]},
        {"domains": ["domain3"], "retweeted": retweeted_uid},
        {"domains": ["domain4"], "quoted": quoted_uid},
        ...
    ],
    uid2: [
        ...
    ],
    ...
}
&lt;/pre>
&lt;/p>
&lt;p>
That is, for each sharing action we have:
&lt;/p>
&lt;p>
&lt;ul>
    &lt;li>the list of domains from which links were shared&lt;/li>
    &lt;li>if the tweet was a retweet, the ID of the user who created the original tweet&lt;/li>
    &lt;li>if the tweet was quoting another tweet, the ID of the user who is being quoted&lt;/li>
&lt;/ul>
&lt;/p>
&lt;p>
All user IDs were anonymized and will not be traceable to Twitter user IDs.
&lt;/p>
&lt;p>
The tweets were collected from the &lt;a href="https://osome.iu.edu/tools/">Social Media Observatory at Indiana University&lt;/a>.
&lt;/p>
&lt;p>
2. &lt;em>anonymized_friends.json&lt;/em>: For each user in the dataset, the list of their friends (followees) as given by the &lt;a href="https://developer.twitter.com/en/docs/twitter-api/v1/accounts-and-users/follow-search-get-users/api-reference/get-friends-ids">friends/ids Twitter API endpoint&lt;/a>.
&lt;/p>
&lt;p>
The format is as follows:
&lt;/p>
&lt;p>
&lt;pre>
{
    uid1: [friend_uid1, friend_uid2, ...],
    uid2: [...],
    ...
}
&lt;/pre>
&lt;/p>
&lt;p>3. &lt;em>measures.tab&lt;/em>: TAB-separated file with partisanship and misinformation scores for each anonymized user.
&lt;p>
All user IDs were anonymized and will not be traceable to Twitter user IDs.
&lt;/p></abstract><sumDscr/></stdyInfo><method><dataColl><sources><dataSrc>Observatory on Social Media, https://osome.iu.edu/tools/</dataSrc><dataSrc>Twitter, https://developer.twitter.com/</dataSrc></sources></dataColl><anlyInfo/></method><dataAccs><setAvail/><useStmt/><notes type="DVN:TOU" level="dv">&lt;a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0&lt;/a></notes></dataAccs><othrStdyMat><relPubl><citation><titlStmt><titl>Dimitar Nikolov, Alessandro Flammini, Filippo Menczer; Right and left, partisanship predicts vulnerability to misinformation; 2021</titl><IDNo agency="arXiv">2010.01462</IDNo></titlStmt><biblCit>Dimitar Nikolov, Alessandro Flammini, Filippo Menczer; Right and left, partisanship predicts vulnerability to misinformation; 2021</biblCit></citation><ExtLink URI="https://arxiv.org/abs/2010.01462"/></relPubl></othrStdyMat></stdyDscr><fileDscr ID="f4972578" URI="https://dataverse.harvard.edu/api/access/datafile/4972578"><fileTxt><fileName>measures.tab</fileName><dimensns><caseQnty>15056</caseQnty><varQnty>3</varQnty></dimensns><fileType>text/tab-separated-values</fileType></fileTxt><notes level="file" type="VDC:UNF" subject="Universal Numeric Fingerprint">UNF:6:Avb9rregQyEFA8q65GDGWA==</notes><notes level="file" type="DATAVERSE:FILEDESC" subject="DataFile Description">Misinformation and partisanship scores for each anonymized user ID.</notes></fileDscr><dataDscr><var ID="v25281671" name="ID" intrvl="discrete"><location fileid="f4972578"/><labl level="variable">ID</labl><sumStat type="medn">68839.5</sumStat><sumStat type="mean">68755.48764612117</sumStat><sumStat type="mode">.</sumStat><sumStat type="invd">0.0</sumStat><sumStat type="vald">15056.0</sumStat><sumStat type="max">137550.0</sumStat><sumStat type="min">5.0</sumStat><sumStat type="stdev">39736.63633798204</sumStat><varFormat type="numeric"/><notes subject="Universal Numeric Fingerprint" level="variable" type="Dataverse:UNF">UNF:6:d8vpOapQiK8cfYpn46o9tQ==</notes></var><var ID="v25281670" name="Partisanship" intrvl="contin"><location fileid="f4972578"/><labl level="variable">Partisanship</labl><sumStat type="mean">0.01853709809571381</sumStat><sumStat type="min">-0.9037</sumStat><sumStat type="medn">-0.04890428489263803</sumStat><sumStat type="vald">15056.0</sumStat><sumStat type="max">0.97121</sumStat><sumStat type="stdev">0.24763640267175</sumStat><sumStat type="invd">0.0</sumStat><sumStat type="mode">.</sumStat><varFormat type="numeric"/><notes subject="Universal Numeric Fingerprint" level="variable" type="Dataverse:UNF">UNF:6:tKjtDUtPYDD5fy2JF/QVuA==</notes></var><var ID="v25281669" name="Misinformation" intrvl="contin"><location fileid="f4972578"/><labl level="variable">Misinformation</labl><sumStat type="min">0.0</sumStat><sumStat type="invd">0.0</sumStat><sumStat type="mean">0.1886755263467546</sumStat><sumStat type="vald">15056.0</sumStat><sumStat type="max">1.0</sumStat><sumStat type="stdev">0.169375625964505</sumStat><sumStat type="medn">0.14634146341463414</sumStat><sumStat type="mode">.</sumStat><varFormat type="numeric"/><notes subject="Universal Numeric Fingerprint" level="variable" type="Dataverse:UNF">UNF:6:3kAFHQNqZT2evOQ3Ad7vwg==</notes></var></dataDscr><otherMat ID="f4104386" URI="https://dataverse.harvard.edu/api/access/datafile/4104386" level="datafile"><labl>anonymized-friends.json</labl><txt>Twitter friends</txt><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">application/json</notes></otherMat><otherMat ID="f4104385" URI="https://dataverse.harvard.edu/api/access/datafile/4104385" level="datafile"><labl>anonymized-shares.json</labl><txt>Sharing actions</txt><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">application/json</notes></otherMat></codeBook>