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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2023
Data sources: Datacite
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2023
Data sources: Datacite
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2023
Data sources: ZENODO
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Monthly Samples of German Tweets (2019 - 2022)

Authors: Nane Kratzke;

Monthly Samples of German Tweets (2019 - 2022)

Abstract

Due to size limitations, this dataset is no longer updated. Further data as of January 2013 can be found in this dataset: https://doi.org/10.5281/zenodo.7670097 This dataset contains German tweets and Twitter accounts recorded from the public Twitter Streaming API using the following filters: terms: 'a', 'e', 'i', 'o', 'u', and 'n' language: 'de' This filter combination should record a 1% sample of (almost) all German tweets (in German it is very unlikely that terms do not contain vowels or the frequently used character 'n'). This dataset might be useful for the following use cases: Natural language processing (focussing on Twitter specifics in German, there exist only little German datasets) Social Network Analysis (Twitter network) Identifying behavioural patterns (retweeting, quoting, replying, hate speech, ...) Sharing political (or other domain-specific) content Bot detection and more ... This dataset will be updated monthly. Each sample (starting in April 2019) will follow the following naming pattern: german-tweet-sample-<YEAR>-<MONTH>.zip (size: ~ 1GB) It will contain several bunches of recorded JSON gzipped files.

Related Organizations
Keywords

Twitter, dataset, German

EOSC Subjects

Twitter Data

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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!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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