About Prompt
- Prompt Type – Dynamic
- Prompt Platform – ChatGPT, Grok, Deepseek, Gemini, Copilot, Midjourney, Meta AI and more
- Niche – Sentiment Analysis
- Language – English
- Category – Market Research
- Prompt Title – AI Prompt for Analyzing Viewer Sentiment from Social Media About a Movie
Prompt Details
This prompt is designed to be dynamic, allowing for customization across different movies, social media platforms, and specific aspects of market research. It follows best practices for AI prompt engineering, aiming for detailed and specific instructions to maximize output quality and relevance.
**Base Prompt:**
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Analyze viewer sentiment towards the movie “[MOVIE TITLE]” on social media platform(s) “[SOCIAL MEDIA PLATFORMS]” for market research purposes. Focus on posts from the period “[DATE RANGE]” (or specify “since release” for ongoing analysis).
Consider the following aspects:
* **Overall Sentiment:** Determine the general positive, negative, or neutral sentiment towards the movie. Quantify the sentiment distribution (e.g., percentage positive, negative, neutral).
* **Key Themes & Drivers:** Identify recurring themes, opinions, and emotions expressed about the movie. What aspects of the movie are driving positive or negative sentiment (e.g., plot, acting, special effects, marketing)? Provide specific examples from social media posts to illustrate these themes.
* **Demographic Insights (if available):** Analyze sentiment variation across different demographic groups (e.g., age, gender, location) if the platform provides such data. Are there significant differences in how various demographics perceive the movie?
* **Comparison with Competitors (optional):** If relevant, compare the sentiment towards “[MOVIE TITLE]” with that of its direct competitors (e.g., movies in the same genre released around the same time). Specify competitor movie titles if applicable.
* **Market Research Implications:** Based on the sentiment analysis, what are the potential implications for the movie’s marketing and distribution strategy? What opportunities or challenges does the sentiment data present? For example, are there specific demographics that require targeted marketing efforts? Are there negative perceptions that need to be addressed through public relations or adjustments to future marketing campaigns?
* **Output Format:** Present the analysis in a structured format, using headings, bullet points, and clear language. Include quantifiable data whenever possible (e.g., percentage distributions, sentiment scores). Provide specific examples from social media posts to support your findings.
**Dynamic Parameters:**
The following parameters should be replaced with specific values for each analysis:
* **[MOVIE TITLE]:** The title of the movie being analyzed (e.g., “Avengers: Endgame”).
* **[SOCIAL MEDIA PLATFORMS]:** The social media platform(s) to be analyzed (e.g., “Twitter, Instagram, YouTube”).
* **[DATE RANGE]:** The specific time period for analysis (e.g., “2023-10-26 to 2023-11-26” or “since release”).
* **[COMPETITOR MOVIE TITLES] (Optional):** Titles of competitor movies for comparison (e.g., “Dune,” “The Matrix Resurrections”).
**Advanced Prompt Customization (Optional):**
For more granular analysis, you can add the following parameters or instructions:
* **Specific Aspects:** Focus the sentiment analysis on particular aspects of the movie (e.g., “Analyze sentiment related to the movie’s ending,” “Analyze sentiment towards the performance of a specific actor”).
* **Sentiment Scoring System:** Specify a desired sentiment scoring system (e.g., -1 to +1, 1 to 5 stars). This helps standardize results across different analyses.
* **Keywords/Hashtags:** Include relevant keywords or hashtags to refine the search and focus on specific conversations (e.g., “#MovieReview,” “#[MovieTitle]Review”).
* **Language Filtering:** Specify the language(s) of the social media posts to be analyzed (e.g., “English,” “Spanish”).
* **Location Filtering:** Restrict the analysis to specific geographic locations if relevant to the market research (e.g., “United States,” “United Kingdom”).
**Example Usage:**
“Analyze viewer sentiment towards the movie “Dune: Part Two” on social media platforms “Twitter, Reddit” since release. Compare it with the sentiment towards its competitor “Avatar: The Way of Water.” Focus on sentiment related to the visual effects and world-building. Output the analysis in a structured format with quantifiable data and specific examples.”
By using this dynamic prompt and customizing it with the specific parameters, you can effectively leverage AI for comprehensive movie viewer sentiment analysis, providing valuable insights for market research and decision-making.
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