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Cited by 60Social Media and PoliticsComputational and Text Analysis MethodsSentiment Analysis and Opinion Mining

When Politicians Talk: Assessing Online Conversational Practices of Political Parties on Twitter

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Lietz, Haiko, Wagner, Claudia, Bleier, Arnim, Strohmaier, Markus·2014·Proceedings of the International AAAI Conference on Web and Social Media
DOI 10.1609/icwsm.v8i1.14521
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Abstract

Assessing political conversations in social media requires a deeper understanding of the underlying practices and styles that drive these conversations. In this paper, we present a computational approach for assessing online conversational practices of political parties. Following a deductive approach, we devise a number of quantitative measures from a discussion of theoretical constructs in sociological theory. The resulting measures make different – mostly qualitative – aspects of online conversational practices amenable to computation. We evaluate our computational approach by applying it in a case study. In particular, we study online conversational practices of German politicians on Twitter during the German federal election 2013. We find that political parties share some interesting patterns of behavior, but also exhibit some unique and interesting idiosyncrasies. Our work sheds light on (i) how complex cultural phenomena such as online conversational practices are amenable to quantification and (ii) the way social media such as Twitter are utilized by political parties.

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  • Previous studies reveal that homophily of the aggregate network measured using retweeting and mentioning tend to be the same, although mentioning is more volatile at the group levels.

    “Previous studies (Lietz et al., 2014;Aragón et al., 2013) reveal that homophily of the aggregate network measured using retweeting and mentioning tend to be same, although mentioning is more volatile at the group (sub network with a particular ideology) levels.”

    From Credibility of climate change denial in social media (2019) · cites this paper as Lietz et al., 2014

    The Introduction (page unavailable) says that homophily is weakest for mentioning and that its variance across parties is largest, supporting the claim about greater group-level variation. It does not establish that aggregate homophily is the same for retweeting and mentioning; its comparison instead emphasizes a difference between them. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Lietz, H., Wagner, C., Bleier, A., & Strohmaier, M.
Affiliations
GESIS - Leibniz Institute for the Social Sciences (DE)
ORCID
Venue
Proceedings of the International AAAI Conference on Web and Social Media
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Published
2014-05-16
Volume
8
Issue
1
Pages
285-294
ISSN
  • 2162-3449 (ISSN-L)
  • 2334-0770
DOI
10.1609/icwsm.v8i1.14521
OpenAlex
W1594182567
Cited by
60
References
2
Citations by year
2026: 1 · 2024: 2 · 2023: 5 · 2022: 4 · 2021: 7 · 2020: 2 · 2019: 8 · 2018: 8 · 2017: 6 · 2016: 9 · 2015: 5 · 2014: 3
FWCI
19.45
Type
conference paper
Language
en
Open access
Locations
  • Proceedings of the International AAAI Conference on Web and Social Media (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • Social Science Open Access Repository (GESIS – Leibniz Institute for the Social Sciences) (submittedVersion)
  • AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) (submittedVersion)
  • RWTH Publications (RWTH Aachen) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Social Sciences › Communication › Social Media and Politics
  • Social Sciences › General Social Sciences › Computational and Text Analysis Methods
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
Keywords
political parties, Twitter, politicians, social media, quantitative indicators, sociological theory, political communication

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