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Cited by 172

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

AN INVESTIGATION OF INFLUENTIALS AND THE ROLE OF SENTIMENT IN POLITICAL COMMUNICATION ON TWITTER DURING ELECTION PERIODS

Dang-Xuan, Linh, Stieglitz, Stefan, Wladarsch, Jennifer, Neuberger, Christoph·2013·Information, Communication & Society

Abstract

In this paper, the authors investigate how Twitter is used for political communication during election periods with a specific focus on characteristics and communication behavior of influential accounts. Our analysis focuses on the state parliament election in Berlin (Germany) on 18 September 2011. Tweets of the top-30 most retweeted users are analyzed with respect to content-related features such as emotionality, appraisal of political parties or politicians, and topics. Furthermore, the authors test hypotheses regarding the relationship between sentiment in terms of emotionality and appraisals occurring in tweets and their quantity and speed of dissemination. Our work helps both researchers and politicians to better understand the nature of influentials in political communication and the role of sentiment in information diffusion on Twitter.

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Metadata

Authors
Dang-Xuan, L., Stieglitz, S., Wladarsch, J., & Neuberger, C.
Venue
Information, Communication & Society
Published
2013-06
Volume
16
Issue
5
Pages
795-825
ISSN
  • 1369-118X (ISSN-L)
  • 1468-4462
OpenAlex
W2163081192
Cited by
172
References
9
FWCI
31.81
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: AN INVESTIGATION OF INFLUENTIALS AND THE ROLE OF SENTIMENT IN POLITICAL COMMUNICATION ON TWITTER DURING ELECTION PERIODS. https://app.cochat.ai/papers/10.1080/1369118x.2013.783608
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Dang-Xuan, L., Stieglitz, S., Wladarsch, J., & Neuberger, C. (2013). AN INVESTIGATION OF INFLUENTIALS AND THE ROLE OF SENTIMENT IN POLITICAL COMMUNICATION ON TWITTER DURING ELECTION PERIODS. Information, Communication & Society. https://doi.org/10.1080/1369118x.2013.783608

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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