Dynamic evolution monitoring of brand sentiment based on causal discovery neural networks

Key Points

• This research aims to examine how brand sentiment evolves over time using causal discovery neural networks.
• Utilized causal discovery neural networks to analyze brand sentiment data.
• Monitored changes in sentiment dynamically over specified time intervals.
• Employed data analysis techniques to assess trends in brand perception.
• Identified key factors driving changes in brand sentiment.
• Showed significant fluctuations in sentiment based on external influences.
• Revealed patterns of sentiment evolution that can inform branding strategies.