Authors:
Lisa Grobelscheg
1
;
2
;
Ema Kušen
2
and
Mark Strembeck
3
;
4
;
2
Affiliations:
1
FH CAMPUS 02 , University of Applied Sciences, Graz, Austria
;
2
Vienna University of Economics and Business, Vienna, Austria
;
3
Complexity Science Hub (CSH), Vienna, Austria
;
4
Secure Business Austria (SBA), Vienna, Austria
Keyword(s):
Narratives, Online Social Networks, Social Bots, Topic Modeling, Twitter.
Abstract:
A narrative is a set of topic-wise interconnected messages that have been sent/posted via a social media platform. In recent years, social media play an important role in human information seeking behavior during and shortly after crisis events. Moreover, automated accounts (so called social bots) have been identified to play an instrumental role in manipulating the public discourse on social media. In this paper, we investigate the impact of bot accounts on the Twitter discourse surrounding the terror attack that took place in Vienna, Austria, on November 2nd 2020. The corresponding data-set consists of 399,247 tweets. In our analysis, we derive a structural topic model and map it to the five “narratives of crisis” as proposed by Seeger and Sellnow. Among other things, we were able to identify bot activity in neutral as well as in negative narratives, including breaking news updates, finger pointing, and expressions of shock and grief. Positive narratives, such as stories of heroes,
were predominantly driven by human users. In addition, we found that the bots contributing to narratives surrounding the Vienna terror attack did not have the ability of picking up local story lines and contributed to more global narratives instead. Moreover, we identified similar temporal patterns in narratives with high bot involvement.
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