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1. This study identifies the key parameters in a model of online rumors that affect the upper growth limit of online public opinion.
2. The logistic population growth model is used to analyze the mechanism underlying the impact of online rumors on the information quantity of online public opinion.
3. Numerical simulations are performed to explore the development trend of the information quantity of online public opinion under the control of three parameters: rumor input rate, rumor conversion rate and rumor refutation rate.
This article provides an analysis of how online rumors can affect the upper growth limit of online public opinion, using a statistical model based on logistic population growth models and differential equations. The article is well-structured and provides a clear overview of its main points, as well as detailed explanations for each point. The authors provide evidence for their claims by citing relevant research studies and providing numerical simulations to support their conclusions.
The article does not appear to be biased or one-sided in its reporting, as it presents both sides equally and acknowledges potential risks associated with its conclusions. However, there are some missing points that could have been explored further, such as how different types of rumors may have different impacts on public opinion or how other factors such as education level may influence rumor refutation rates. Additionally, there is no discussion about possible counterarguments or alternative perspectives that could be taken into consideration when assessing the impact of online rumors on public opinion.
In conclusion, this article provides a comprehensive overview of how online rumors can affect the upper growth limit of online public opinion and offers useful insights into potential strategies for controlling rumors. While there are some missing points that could have been explored further, overall this article appears to be reliable and trustworthy in its reporting.