Strategies and Influence of Social Bots in a 2017 German state election - A case study on Twitter
October 20, 2017 Β· Declared Dead Β· π ACIS
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Florian Brachten, Stefan Stieglitz, Lennart Hofeditz, Katharina Kloppenborg, Annette Reimann
arXiv ID
1710.07562
Category
cs.CY: Computers & Society
Cross-listed
cs.HC
Citations
37
Venue
ACIS
Last Checked
6 months ago
Abstract
As social media has permeated large parts of the population it simultaneously has become a way to reach many people e.g. with political messages. One way to efficiently reach those people is the application of automated computer programs that aim to simulate human behaviour - so called social bots. These bots are thought to be able to potentially influence users' opinion about a topic. To gain insight in the use of these bots in the run-up to the German Bundestag elections, we collected a dataset from Twitter consisting of tweets regarding a German state election in May 2017. The strategies and influence of social bots were analysed based on relevant features and network visualization. 61 social bots were identified. Possibly due to the concentration on German language as well as the elections regionality, identified bots showed no signs of collective political strategies and low to none influence. Implications are discussed.
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