Sentiment analysis

Marketing Analytics for Business

Sarah DeAtley

Principal Data Scientist

Sentiment analysis basics

 

image showing happy, neutral, and sad face with checkboxes

  • Brands advertise on social media platforms like Twitter, Instagram, and Facebook
  • One way to monitor social media health is through sentiment analysis

 

Sentiment analysis: technique to determine if data is positive, negative, or neutral

1 athree23 from Pixabay
Marketing Analytics for Business

Sentiment complexity

  • Sentiment is subjective! Brands want to monitor in real-time
  • Context is key:
    • "Well done" in sports has a different meaning than in restaurants
  • Sentiment can be more than positive, negative, or neutral:
    • Angry, happy, or sad
    • Urgent or non-urgent
  • Also consider emojis and sarcasm

image of steak on the left and golfers on the right with text "well done"

various emojis with label "reactions"

1 Denis Cherkashin on Unsplash
Marketing Analytics for Business

Sentiment model types

  • Manual: analyst applies rules to data
  • Automatic: NLP automatically determines sentiment
  • Evaluate level of complexity and data size:
    • Automatic for large data sets with multiple languages
    • Manual for ease of interpretation with smaller data
  • Manual rules can train automatic NLP models (hybrid approach)

 

man scratching head looking at paper with happy, neutral, and smiling faces

1 mohamed Hassan from Pixabay
Marketing Analytics for Business

NLP model options

 

various charts in a dashboard

  • NLP model options:

    • Out-of-the-box model with NLP sentiment
    • Build and maintain in-house NLP sentiment model
  • Still learning about NLP? Start with out-of-the-box model

  • Experience training NLP models? In-house has more flexibility
  • Consider long term reporting needs with both options!
1 Carlos Muza on Unsplash
Marketing Analytics for Business

Let's practice!

Marketing Analytics for Business

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