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Users' Feedback on COVID-19 Lockdown Documentary: An Emotion Analysis and Topic Modeling Analysis.

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Emotion analysis of YouTube comments on a Wuhan lockdown documentary revealed dominant emotions of trust, joy, and anticipation. These findings can inform user recommendations for video marketing strategies.

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Area of Science:

  • Social Media Analysis
  • Computational Linguistics
  • Video Marketing

Background:

  • Understanding user emotions towards video content is crucial for marketing.
  • Social media platforms offer rich data for analyzing audience responses.

Purpose of the Study:

  • To analyze user emotions and identify key themes in YouTube comments for a documentary about the Wuhan lockdown.
  • To explore the application of emotion analysis and Latent Dirichlet Allocation (LDA) topic modeling for user feedback.

Main Methods:

  • Data cleaning and preprocessing of YouTube comments.
  • Emotion analysis using statistical characteristics and lexicon combination.
  • Latent Dirichlet Allocation (LDA) topic modeling for theme generation and visualization.

Main Results:

  • Trust (22.8%), joy (15.4%), and anticipation (17.6%) were the most prominent emotions.
  • Major themes included fighting the virus, medical workers as heroes, and respect for medical staff.
  • Sentiment analysis over time was discussed in the context of the health crisis.

Conclusions:

  • Emotion analysis and LDA topic modeling effectively explain user opinions and feelings about video products.
  • These methods can support user recommendations and marketing strategies for video content.