Sign In
Sentiment Analysis Prompt
by Natalia C test
0
Prompt
<100
Summary
Summary
Analyzes the emotional tone of social media interactions, providing insights into audience sentiment towards brands and content.
Overview
Overview
This prompt utilizes advanced natural language processing techniques to evaluate the sentiment expressed in social media posts, comments, and interactions. It helps businesses understand how their audience feels about their brand, products, or services, enabling data-driven decision-making in social media strategy.
System Prompt
System Prompt
You are an expert in social media sentiment analysis. Your task is to analyze the emotional tone of social media interactions, providing insights into audience sentiment towards brands and content. Consider the context, language nuances, and any relevant emojis or hashtags in your analysis. Categorize the sentiment as positive, negative, or neutral, and provide a brief explanation for your assessment.
User Prompt
User Prompt
Analyze the sentiment of the following social media post about Brand Name
Brand Name 's customer service is unbelievable! I've been waiting for a response for 3 days now. 😡 #disappointedcustomer"
Sample Response
Sample Response
Sentiment: Negative
Analysis: The post expresses strong negative sentiment towards [Brand Name]'s customer service. Key indicators include:
- Sarcasm: The use of "unbelievable" is likely sarcastic given the context.
- Complaint: The user mentions waiting for 3 days for a response, indicating poor service.
- Angry emoji: The use of the angry face emoji (😡) reinforces the negative emotion.
- Negative hashtag: #disappointedcustomer clearly expresses dissatisfaction.
Overall, this post reflects very unfavorable sentiment, suggesting the brand needs to improve its customer service response time to address customer frustration.
Features
Features
- Multi-platform analysis: Can analyze posts from various social media platforms.
- Contextual understanding: Considers the broader context of the post for accurate sentiment assessment.
- Emoji and hashtag interpretation: Incorporates the sentiment conveyed by emojis and hashtags.
- Sarcasm detection: Attempts to identify and correctly interpret sarcastic statements.
- Sentiment categorization: Classifies sentiment as positive, negative, or neutral.
- Explanation generation: Provides reasoning behind the sentiment assessment.
- Brand mention tracking: Identifies and analyzes posts mentioning specific brands or products.
- Trend analysis: Can track sentiment changes over time when applied to multiple posts.
License & Privacy
MIT
Privacy Terms
Technical
Updated
September 23, 2024Works with
GenAI Activities
Model Recommended
GPT-3
Tags
Support
UiPath Community Support
Similar Listings
