학술논문

The Effect of Message Repetition on Information Diffusion on Twitter: An Agent-Based Approach
Document Type
Periodical
Source
IEEE Transactions on Professional Communication IEEE Trans. Profess. Commun. Professional Communication, IEEE Transactions on. 66(2):150-169 Jun, 2023
Subject
General Topics for Engineers
Engineering Profession
Social networking (online)
Blogs
Web sites
Information processing
TV
Media
Information exchange
Information sharing
Message passing
Information quality
Market research
Consumer behavior
Consumer satisfaction
Agent-based model
information diffusion
Twitter
wear-out effect
Language
ISSN
0361-1434
1558-1500
Abstract
Background: Twitter offers tools that facilitate the diffusion of information by which companies can engage consumers to share their messages. Literature review: Communication professionals are using platforms such as Twitter to disseminate information; however, the strategies that they should use to achieve high information diffusion are not clear. This article proposes message repetition as a strategy. Research questions: 1. What is the wear-out point of Twitter? 2. How many times should a company repeat a tweet written on its brand page to maximize the diffusion for seeds? 3. How many times should a company repeat a tweet written on its brand page to maximize the diffusion while minimizing the number of consumers reaching their wear-out point for seeds? 4. How many times should a company repeat a tweet written on its brand page to maximize the diffusion for nonseeds? 5. How many times should a company repeat a tweet written on its brand page to maximize the diffusion while minimizing the number of consumers reaching their wear-out point for both seeds and nonseeds? Research methodology: An agent-based simulation model for information diffusion is proposed as an approach to measure the diffusion of a tweet that has been repeated. The model considers that consumers can reach their wear-out point when they read a tweet several times. Results: The results of the model indicate the number of times a company should send the same tweet to achieve high information diffusion before this action has negative effects on consumers. Brand followers are key to achieving high information diffusion; however, consumers begin to feel bothered by the tweet by the sixth repetition. Conclusions: To the best of our knowledge, this is the first study to examine tweet repetition as a strategy to achieve higher information diffusion on Twitter. In addition, it extends the information diffusion literature by controlling the wear-out effect. It contributes to both communication and computational science literature by analyzing a communication problem using an agent-based approach. Finally, this article contributes to the field of technical and professional communication by testing a strategy to reach great information diffusion, and by creating a tool that any company can use to anticipate the results of a communication campaign created in Twitter before launching it.