Brexit and bots: characterizing the behaviour of automated accounts on Twitter during the UK election
arXiv:2107.14155 · doi:10.1140/epjds/s13688-022-00330-0
Abstract
Online Social Networks represent a novel opportunity for political campaigns, revolutionising the paradigm of political communication. Nevertheless, many studies uncovered the presence of d/misinformation campaigns or of malicious activities by genuine or automated users, putting at severe risk the credibility of online platforms. This phenomenon is particularly evident during crucial political events, as political elections. In the present paper, we provide a comprehensive description of the structure of the networks of interactions among users and bots during the UK elections of 2019. In particular, we focus on the polarised discussion about Brexit on Twitter analysing a data set made of more than 10 million tweets posted for over a month. We found that the presence of automated accounts fostered the debate particularly in the days before the UK national elections, in which we find a steep increase of bots in the discussion; in the days after the election day, their incidence returned to values similar to the ones observed few weeks before the elections. On the other hand, we found that the number of suspended users (i.e. accounts that were removed by the platform for some violation of the Twitter policy) remained constant until the election day, after which it reached significantly higher values. Remarkably, after the TV debate between Boris Johnson and Jeremy Corbyn, we observed the injection of a large number of novel bots whose behaviour is markedly different from that of pre-existing ones. Finally, we explored the bots' stance, finding that their activity is spread across the whole political spectrum, although in different proportions, and we studied the different usage of hashtags by automated accounts and suspended users, thus targeting the formation of common narratives in different sides of the debate.
arXiv comment18 pages, 13 figures
References in corpus (28)
- Fast unfolding of communities in large networks
- Community detection in graphs
- Functional cartography of complex metabolic networks
- The science of fake news
- Near linear time algorithm to detect community structures in large-scale networks
- The Rise of Social Bots
- The spread of low-credibility content by social bots
- The statistical mechanics of networks
- Bots increase exposure to negative and inflammatory content in online social systems
- Disinformation and Social Bot Operations in the Run Up to the 2017 French Presidential Election
- Fame for sale: efficient detection of fake Twitter followers
- The Statistical Physics of Real-World Networks
- Online Human-Bot Interactions: Detection, Estimation, and Characterization
- Analytical maximum-likelihood method to detect patterns in real networks
- Maximum likelihood: extracting unbiased information from complex networks
- Social Fingerprinting: detection of spambot groups through DNA-inspired behavioral modeling
- Randomizing bipartite networks: the case of the World Trade Web
- Detection of Novel Social Bots by Ensembles of Specialized Classifiers
- Inferring monopartite projections of bipartite networks: an entropy-based approach
- The role of bot squads in the political propaganda on Twitter
- No Echo in the Chambers of Political Interactions on Reddit
- Flow of online misinformation during the peak of the COVID-19 pandemic in Italy
- Fast and scalable likelihood maximization for Exponential Random Graph Models with local constraints
- Spotting political social bots in Twitter: A use case of the 2019 Spanish general election
- Extracting significant signal of news consumption from social networks: the case of Twitter in Italian political elections
- Networked partisanship and framing: a socio-semantic network analysis of the Italian debate on migration
- On the efficacy of old features for the detection of new bots
- Effectiveness of dismantling strategies on moderated vs. unmoderated online social platforms
Cited by in corpus (7)
- Bow-Tie Structures of Twitter Discursive Communities
- Pattern detection in bipartite networks: a review of terminology, applications and methods
- Entropy-based detection of Twitter echo chambers
- Design and analysis of tweet-based election models for the 2021 Mexican legislative election
- From chambers to echo chambers: Quantifying polarization with a second-neighbor approach applied to Twitter's climate discussion
- Investigation into the Spread of Misinformation about UK Prime Ministers on Twitter
- Leveraging Content Producer Networks and User Perception to Detect Online Discursive Communities