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Dataset . 2019
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Data sources: Datacite
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ZENODO
Dataset . 2019
License: CC BY NC SA
Data sources: Datacite
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ZENODO
Dataset . 2019
License: CC BY NC SA
Data sources: ZENODO
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ZENODO
Dataset . 2019
License: CC BY NC SA
Data sources: Datacite
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ZENODO
Dataset . 2019
License: CC BY NC SA
Data sources: ZENODO
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Domain shares on Twitter containing news and misinformation

Authors: Nikolov, Dimitar; Menczer, Filippo;

Domain shares on Twitter containing news and misinformation

Abstract

This dataset contains a set of domain sharing actions that occurred on Twitter during the month of June 2017. Each domain sharing action can be thought of as a triple (user_id, action_id, domain). The user_id is an anonymized Twitter account ID, and the action_id is an anonymized tweet ID. The tweets from which the dataset was created were collected through Twitter's decahose API. Each user in the dataset was responsible for sharing at least one news article, and at least one article that can be labeled as misinformation. The data is distributed in domain-shares.data in the following JSON format: { "<user-id>": { "<action-id>": ["<domain>", "<domain>", ...], ... }, ... } For example: { "22359b28-93e1-4c13-a3eb-e72357b77c65": { "1": ["palmerreport.com"], "2": ["reuters.com", "abcn.ws"], "3": ["mobile.nytimes.com"] }, "ffe79a32-d49d-4780-87b7-bb6417106067": { "4": ["dallasnews.com"] } } In addition, a TAB-separated version with (user id, action id, domain) triples is also available. For further information on how the dataset was constructed and on analyses that have been conducted on it, please refer to the accompanying Github repository at https://github.com/dimitargnikolov/twitter-bias.

Related Organizations
Keywords

fake news, bias, social media, twitter, news, misinformation

EOSC Subjects

Twitter Data

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download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
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12
5