2017/10/20 by Florian Brachten, Stefan Stieglitz, Brachten, Florian +7
Computer Science · Social Sciences · #Computers and Society (cs.CY) #FOS: Computer and information sciences #Hate Speech and Cyberbullying Detection #Human-Computer Interaction (cs.HC) #Misinformation and Its Impacts #Social Media and Politics #Spam and Phishing Detection
paper · pdf · doi:10.48550/arxiv.1710.07562
openalex publication_date 2017/10/20 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
As social media has permeated large parts of the population it simultaneously\nhas become a way to reach many people e.g. with political messages. One way to\nefficiently reach those people is the application of automated computer\nprograms that aim to simulate human behaviour - so called social bots. These\nbots are thought to be able to potentially influence users' opinion about a\ntopic. To gain insight in the use of these bots in the run-up to the German\nBundestag elections, we collected a dataset from Twitter consisting of tweets\nregarding a German state election in May 2017. The strategies and influence of\nsocial bots were analysed based on relevant features and network visualization.\n61 social bots were identified. Possibly due to the concentration on German\nlanguage as well as the elections regionality, identified bots showed no signs\nof collective political strategies and low to none influence. Implications are\ndiscussed.\n