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Improving information spread by spreading groups
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DOI：10.1108/OIR-08-2018-0245.png)
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Abstract
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Purpose The purpose of this paper is to propose a novel method to enhance the spread of messages in social networks by Spreading Groups. These sub-structures of highly connected accounts intentionally echo messages between the members of the subgroup at the early stages of a spread. This echoing further boosts the spread to regions substantially larger than the initial region. These spreading accounts can be actual humans or social bots. Design/methodology/approach The paper reveals an interesting anomaly in information cascades in Twitter and proposes the spreading group model that explains this anomaly. The model was tested using an agent-based simulation, real Twitter data and questionnaires. Findings The messages of few anonymous Twitter accounts spread on average more than well-known global financial media groups, such as The Wall Street Journal or Bloomberg. The spreading groups (also sometimes called BotNets) model provides an effective mechanism that can explain these findings. Social implications With the blossoming of fake news, one might tend to assess the reliability of news by the number of users involved in its spread. This heuristic might be easily fooled by spreading groups. Furthermore, spreading groups consisting of a blend of human and computerized bots might be hard to detect. They can be used to manipulate financial markets or political campaigns. Originality/value The paper demonstrates an anomaly in Twitter that was not studied before. It proposes a novel approach to spreading messages in social networks. The methods presented in the paper are valuable for anyone interested in spreading messages or an agenda such as political actors or other agenda enthusiasts. While social bots have been widely studied, their synchronization to increase the spread is novel.
Keywords:
Information spread
Viral marketing
Social networks
Spreading groups
Fake news
BotNets
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