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https://doi.org/10.5281/zenodo...
Dataset . 2023
License: CC BY NC
Data sources: Sygma
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ZENODO
Dataset . 2023
License: CC BY NC
Data sources: ZENODO
ZENODO
Dataset . 2023
License: CC BY NC
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY NC
Data sources: Datacite
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OKG: A Knowledge Graph for Fine-grained Understanding of Social Media Discourse on Inequality

Authors: Blin, Inès; Stork, Lise; Spillner, Laura; Santagiustina, Carlo Romano Marcello Alessandro;

OKG: A Knowledge Graph for Fine-grained Understanding of Social Media Discourse on Inequality

Abstract

The Observatory Knowledge Graph (OKG) is a knowledge graph with tweets on inequality in terms of the OBIO ontology (https://w3id.org/okg/obio-ontology/), which integrates social media metadata with various types of linguistic knowledge. The OKG can be used as the backbone of a social media observatory, to facilitate a deeper understanding of social media discourse on inequality. We retrieved tweets and retweets published from the end (30th) of May 2020 to the beginning (1st) of May 2023. In this version of the OKG, we use a sample of 85,247 tweets, published from May 30th to August 27th, 2020. To be compliant with Twitter's policies, we remove usernames and id's, as well as the tweet texts and sentences. We also replace user IRIs with skolem IRIs through skolemization. Access to the OKG as well as the SPARQL endpoint can be requested by sending a mail to the contact person (l.stork@uva.nl) with the following information: A description of the use case Affiliation of the researchers involved How their work is in line with Twitter's policies: https://developer.twitter.com/en/developer-terms/policy#4-d

Keywords

Knowledge Graph, Social Media Discourse, Twitter, Social Inequality, Observatory, Natural Language Processing

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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!
0
Average
Average
Average