Sentiment Analysis for Excel

Analyze text sentiment directly in Excel spreadsheets.

Overview

Sentiment analysis classifies text as having positive or negative overall sentiment. Common use cases include customer support, market research, and financial analysis.

Features

Feature Description
💻 Local Analysis runs in your spreadsheet, not the cloud
🤗 Open Source Uses models from Hugging Face
🆓 Free Unlimited free processing
🔒 Private Your data stays in your spreadsheet

Basic Usage

  1. Select a column of text to analyze
  2. Click the Analyze button in the taskpane
  3. Results appear in a new sheet

Advanced Usage

  • Choose from four different sentiment analysis models
  • Optionally split paragraphs into individual sentences

Installation

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Instructions

Getting Started

  1. Install the add-in, then open the taskpane by clicking the 🙂 icon in the ribbon
  2. Select the range of cells containing text to analyze (must be a single column, no row limit)
  3. Click Analyze—a new sheet is added to hold the results

Excel Select Text
  1. On first use, the model downloads from Hugging Face (takes extra time). Subsequent uses are faster as the model is cached in browser storage.
  2. Results appear progressively as analysis runs
  3. Click Cancel at any time to stop and start over

Excel Results

Output Format

Text - Model: Movie Reviews Label Score
I really enjoyed it. POSITIVE 0.99
This is the worst movie I’ve ever seen. NEGATIVE 0.99
I liked Karim, but story was awful. POSITIVE 0.70
Column Description
Text Copy of selected text, with header showing model used
Label Sentiment label (POSITIVE or NEGATIVE)
Score Confidence score (0 to 1). Higher = more confident

Note: In the example above, the model is less confident about the last row because it contains mixed sentiments.

Advanced Options

Toggle Advanced options to reveal:

Option Description
Model selection Choose from Movie Reviews (default, general-purpose), Product Reviews (multi-language), Finance News, or Twitter Messages
Split into sentences Uses sentence boundary detection to analyze individual sentences—useful for paragraphs with mixed sentiments

Tip: We’re exploring Aspect-based Sentiment Analysis as a more powerful solution for mixed-sentiment text.

Demo

YouTube Demo Video