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Sentiment-Based Topic Analysis on Product Demand Prediction: Pre-Release and Post-Release Study

Behrad, Hossein | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57115 (44)
  4. University: Sharif University of Technology
  5. Department: Management and Economics
  6. Advisor(s): Aslani, Shirin
  7. Abstract:
  8. This thesis examines the impact of electronic word-of-mouth (e-WOM) on product demand forecasting, specifically in the context of video game consoles. This study examines the importance of emotion-based topics and their impact on demand forecasting at two stages of the product life cycle: pre-launch and post-launch. Using sentiment analysis and topic modeling, this study uncovers product sales drivers and captures evolving consumer sentiment throughout the product lifecycle. By integrating insights from diffusion theory and consumer information search theory, this research contributes to the field of demand forecasting using social media data. This research shows that by using the topics discussed in the online comments of customers, on average, customers have a more positive feeling towards the product after its release. Also, in the week before the release of the product, a peak in sentiment can be seen in most of the topics, but after the release of the product, we will see a decrease, so the week leading up to the product, we will see the excitement of the customers. We also showed that by using the topics discussed in the comments, the accuracy of the model can be increased by more than 20%. This thesis provides a comprehensive understanding of the dynamic interplay between e-WOM and product demand, providing valuable insights for businesses and researchers seeking to optimize product launch strategies and accurately forecast demand
  9. Keywords:
  10. Electronic Word to Mouth ; Sentiment Analysis ; Topic Modeling ; Demand Forecasting

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