Sentiment

Sentiment refers to the emotional tone or attitude expressed in online conversations about a brand, product, topic, or campaign. Mentions are typically classified as positive, negative, or neutral. Social intelligence platforms employ natural language processing (NLP) and language models to interpret words, phrases, sarcasm, and context so as to assign sentiment labels.

Through sentiment analysis, organizations gain insight into how people feel, not just whether they talk.

Tracking sentiment is critical because it adds qualitative depth to raw volume metrics (like Buzz). Some of its uses:

• Reputation monitoring: A surge of negative sentiment signals risk before a crisis escalates.
  
• Customer feedback: Brands can identify what users appreciate or criticize, and adjust accordingly.
  
• Campaign evaluation: Positive sentiment around a campaign indicates alignment with audience values; negative sentiment requires remediation.
  
• Market perception: Comparing sentiment across competitors reveals strengths and weaknesses in brand image.
  
• Emotional trends: By monitoring sentiment over time, brands can detect shifts in tone (e.g. from excitement to frustration).

If a company launches a new product, service, or campaign, one of the first tasks is to assess how public reactions are framed. By analyzing the emotional tone of mentions across social media, news, blogs, and forums, brands can determine whether online discussion is mostly supportive, critical, or neutral.

For instance, if a campaign gets widespread attention (high buzz) but sentiment is predominantly negative, the brand gains a warning sign to reconsider messaging or tactics. Conversely, mostly positive sentiment suggests the narrative is resonating well with audiences.

Sentiment analysis offers several measurable facets:

• Volume by sentiment: count of positive, negative, and neutral mentions
• Sentiment trends over time: how sentiment changes daily, weekly, monthly
• Sentiment by channel: e.g. positive on Instagram but negative in news articles
• Sentiment by topic or keyword: sentiment around specific features, themes, or campaigns
• Sentiment drivers: words, phrases, or themes that push sentiment upward or downward

• Buzz / mention volume – sentiment adds tone to volume metrics.
• Net Sentiment – a normalized measure that aggregates positive and negative sentiment into a single figure.
• Share of Voice (SoV) – sentiment helps qualify whether share of conversation is favorable or not.
• Impact / Source Impact – a negative mention from a high-authority source may weigh more heavily than many positive mentions from low-reach sources.
• Engagement – sentiment can drive engagement; emotional posts often get more reactions.

• Use transparent and empathetic communication
• Address complaints swiftly via social channels
• Highlight user testimonials and success stories
• Monitor keyword sentiment actively to catch negative shifts
• Tailor content tone to audience preferences and context
• Encourage user-generated content that shares positive experiences

• A consumer goods company used sentiment tracking to identify product complaints shared repeatedly and corrected them before scaling recall.
• A telecom brand monitored sentiment across different markets and adjusted messaging in regions with more negative tone.
• A digital campaign used sentiment insight to pivot mid-campaign when negative reactions outpaced the positives.

• Sentiment = tone behind the conversation, not just mention counts
• It is essential to pair sentiment with metrics like Buzz, SoV, and Impact for full context
• Negative sentiment, even with high buzz, can signal risk; positive sentiment reinforces brand equity
• With Palowise, teams can monitor sentiment in real time, segment it by channel and topic, and correlate it with other KPIs for deeper insights