TY - JOUR

T1 - Emotions and Information Diffusion on Social Media

T2 - A Replication in the Context of Political Communication on Twitter

AU - Hagemann, Linus

AU - Abramova, Olga

N1 - Publisher Copyright: © 2023 by the Association for Information Systems.

PY - 2023/12

Y1 - 2023/12

N2 - 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 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.

AB - 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 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.

KW - Elections

KW - Information Diffusion

KW - Sentiment

KW - Twitter

KW - Informatics

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=85180515648&partnerID=8YFLogxK

U2 - 10.17705/1atrr.00079

DO - 10.17705/1atrr.00079

M3 - Journal articles

AN - SCOPUS:85180515648

VL - 9

JO - AIS Transactions on Replication Research

JF - AIS Transactions on Replication Research

SN - 2473-3458

M1 - 2

ER -