How do you define and measure sentiment?

Our sentiment analysis goes beyond simple positive/negative: **Sentiment Scale** 1. Very Negative (-2) 2. Negative (-1) 3. Neutral (0) 4. Positive (+1) 5. Very Positive (+2) **Analysis Factors** *Linguistic Elements* - Word choice and intensity - Grammatical structures - Punctuation and emphasis - Emoji and emoticon usage - Slang and colloquialisms *Contextual Understanding* - Conversation thread context - Industry-specific language - Cultural references - Sarcastic tone detection - Comparative statements *Cultural Nuances* - Chinese communication norms - Indirect expression patterns - Face-saving language - Regional variations - Generational differences **Confidence Scoring** - Each sentiment assignment includes confidence % - Low-confidence items flagged for review - Ambiguous cases marked appropriately - Multiple interpretation possibilities noted **Aggregation Methods** - Weighted averages (by engagement/reach) - Volume-weighted sentiment - Influencer-weighted sentiment - Time-decay adjusted sentiment - Platform-normalized sentiment **Sentiment Drivers** - Topic-level sentiment breakdown - Aspect-based sentiment (product, service, price) - Emotion categorization (joy, anger, sadness, etc.) - Intent detection (purchase, complaint, inquiry) **Validation** - Human annotation benchmarking - Inter-annotator agreement scores - Regular accuracy audits - Customer feedback incorporation - Continuous model refinement **Output Formats** - Overall sentiment score - Sentiment distribution percentages - Sentiment trend over time - Sentiment by topic/category - Sentiment comparison (vs. competitors) We provide raw sentiment scores and interpreted insights to support both quantitative and qualitative analysis.