Real-Time Stance Detection and Issue Analysis of the 2021 German Federal Election Campaign on Twitter-Reference-Cited by-同舟云学术

Real-Time Stance Detection and Issue Analysis of the 2021 German Federal Election Campaign on Twitter

Published:2022 Issue: Volume: Page:125-146
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Müller Arthur^ORCID,Riedl Jasmin^ORCID,Drews Wiebke^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-15086-9_9

Reference47 articles.

1. Aldayel, A.: Stance detection on social media: state of the art and trends (2021). https://doi.org/10.1016/j.ipm.2021.102597

2. Barbieri, F., Anke, L.E., Camacho-Collados, J.: XLM-T: a multilingual language model toolkit for Twitter (2021). https://arxiv.org/abs/2104.12250v1

3. Bechini, A., Bondielli, A., Ducange, P., Marcelloni, F., Renda, A.: Addressing event-driven concept drift in twitter stream: a stance detection application. IEEE Access 9, 77758–77770 (2021)

4. Beck, P.A.: The electoral cycle and patterns of American politics. Br. J. Polit. Sci. 9(02), 129 (1979). https://doi.org/10.1017/S0007123400001691

5. Bundeswahlleiter: Heft 4 Wahlbeteiligung und Stimmabgabe nach Geschlecht und Altersgruppen. Wahl zum 20. Deutschen Bundestag am 26, 4 Sept 2021 (2022)

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