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The German Bundestag elections are the most important democratic elections of Germany. This dataset comprises Twitter interactions related with German politicians of the most important political parties over several months in the (pre-)phase of the German election campaigns in 2017. The Twitter accounts of 364 politicians (that is approximately half of the German parliament, the German Bundestag) were followed for almost half a year. The collected data comprise of about 10 GB of Twitter raw data generated by more than 120.000 active Twitter users generating more than 1.200.000 tweets during the pre- and hot-phase of the election campaigns for the 19th German Bundestag. The dataset can be used to study how political parties, their followers and supporters make use of social media channels like Twitter in the context of political election campaigns and what kind of content is shared. The following files contain relevant context information: crawled-pages.json contains the URLs of the official party faction websites of the 18th German Bundestag that were crawled to identify the Twitter screennames of German politicians of all Bundestag factions. Because the Alternative für Deutschland (AfD) and the Freie Demokratische Partei (FDP) were not part of the 18th German Bundestag (but it was likely that they will enter the 19th German Bundestag) other official websites were selected to crawl for relevant and representative politicians for these both parties (in case of the AfD this was the website of the directorate of the AfD federal party and the list of members of the European Parliament, in case of the FDP this was the website of the executive committee of the FDP federal party of Germany). followed-accounts.json contains the (manually checked and edited) crawling result of 327 Twitter screennames of politicians that have been observed via the Twitter streaming API to collect this dataset.
Funded via general support for research by Lübeck University of Applied Sciences.
Twitter, politics, election campaign, federal election, German Bundestag, 2017, 19th German Bundestag, dataset, german, natural language processing, NLP
Twitter Data
Twitter, politics, election campaign, federal election, German Bundestag, 2017, 19th German Bundestag, dataset, german, natural language processing, NLP
Twitter Data
| 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). | 1 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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