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Emotions and information diffusion on social media

  • This paper presents a methodological and conceptual replication of Stieglitz and Dang-Xuan’s (2013) investigation of the role of sentiment in information-sharing behavior on social media. Whereas Stieglitz and Dang-Xuan (2013) focused on Twitter communication prior to the state parliament elections in the German states Baden-Wurttemberg, Rheinland-Pfalz, and Berlin in 2011, we test their theoretical propositions in the context of the state parliament elections in Saxony-Anhalt (Germany) 2021. We confirm the positive link between sentiment in a political Twitter message and its number of retweets in a methodological replication. In a conceptual replication, where sentiment was assessed with the alternative dictionary-based tool LIWC, the sentiment was negatively associated with the retweet volume. In line with the original study, the strength of association between sentiment and retweet time lag insignificantly differs between tweets with negative sentiment and tweets with positive sentiment. We also found that the number of anThis paper presents a methodological and conceptual replication of Stieglitz and Dang-Xuan’s (2013) investigation of the role of sentiment in information-sharing behavior on social media. Whereas Stieglitz and Dang-Xuan (2013) focused on Twitter communication prior to the state parliament elections in the German states Baden-Wurttemberg, Rheinland-Pfalz, and Berlin in 2011, we test their theoretical propositions in the context of the state parliament elections in Saxony-Anhalt (Germany) 2021. We confirm the positive link between sentiment in a political Twitter message and its number of retweets in a methodological replication. In a conceptual replication, where sentiment was assessed with the alternative dictionary-based tool LIWC, the sentiment was negatively associated with the retweet volume. In line with the original study, the strength of association between sentiment and retweet time lag insignificantly differs between tweets with negative sentiment and tweets with positive sentiment. We also found that the number of an author’s followers was an essential determinant of sharing behavior. However, two hypotheses supported in the original study did not hold for our sample. Precisely, the total amount of sentiments was insignificantly linked to the time lag to the first retweet. Finally, in our data, we do not observe that the association between the overall sentiment and retweet quantity is stronger for tweets with negative sentiment than for those with positive sentiment.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Linus HagemannORCiD, Olga AbramovaORCiDGND
DOI:https://doi.org/10.17705/1atrr.00079
ISSN:2473-3458
Titel des übergeordneten Werks (Englisch):AIS transactions on replication research
Untertitel (Englisch):a replication in the context of political communication on Twitter
Verlag:AIS
Verlagsort:Atlanta
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:15.12.2023
Erscheinungsjahr:2023
Datum der Freischaltung:22.02.2024
Freies Schlagwort / Tag:Twitter; elections; information diffusion; sentiment
Band:9
Ausgabe:1
Seitenanzahl:19
Erste Seite:1
Letzte Seite:19
Organisationseinheiten:Wirtschafts- und Sozialwissenschaftliche Fakultät / Wirtschaftswissenschaften / Fachgruppe Betriebswirtschaftslehre
DDC-Klassifikation:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Peer Review:Referiert
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