Visualizing Sentiment Trends: Dashboards with Plotly and Streamlit
Sentiment analysis is the process of determining whether a piece of text—like a customer review—is positive, negative, or neutral. Visualizing sentiment trends means tracking how those opinions change over time. Instead of combing through endless reviews, interactive dashboards allow you to spot spikes in positivity or dips in sentiment at a glance.
For marketers, product teams, and business analysts, understanding customer sentiment trends is vital. But turning that data into clear visuals used to require serious technical know-how. That’s where tools like Plotly and Streamlit come in—making it easy to build an interactive sentiment analysis dashboard even if you’re new to coding.
Why Track Sentiment Trends?
Imagine launching a new product feature and watching customer feedback roll in. Without some form of analysis, it’s tough to know whether the change is being celebrated—or criticized.
By tracking sentiment over time, you can:
- Measure reactions to campaigns, updates, or product changes
- Compare how sentiment shifts across different time periods
- Quickly spot emerging issues before they become larger problems
- Highlight improvements in customer experience
In short, sentiment dashboards help you transform scattered feedback into strategic insights.
Tools Overview: Streamlit and Plotly
To bring sentiment trends to life, two beginner-friendly tools are your best allies:
- Plotly is a powerful charting library that creates interactive graphs like line charts, bar graphs, and pie charts. These visualizations respond to user input, so anyone can hover over a data point to get more information or zoom into a specific time frame.
- Streamlit turns your data script into a web app with just a few lines of Python. It handles all the layout and interactivity, so you can focus on your content—not web design.
Together, they make the perfect team for building accessible, shareable sentiment dashboards.
How to Visualize Sentiment Trends Step-by-Step
Let’s walk through the process of building your own dashboard using customer review data.
1. Collect and Clean Your Data
Start by gathering your review data. This could be from a CSV export, survey tool, or online platform. Each entry should include:
- A review text
- A timestamp or date
- Any other relevant metadata (e.g., product category)
Clean the data by removing duplicates, irrelevant reviews, and formatting inconsistencies.
2. Perform Sentiment Analysis
Next, analyze the tone of each review. Sentiment analysis tools (many of which are no-code or low-code) will score each review as positive, negative, or neutral. Some tools even assign numerical scores, like +0.9 for “Love it!” or –0.6 for “Terrible experience.”
Once each review has a sentiment label or score, you can group the results by date.
3. Organize by Time Period
Convert timestamps into common time units—like weekly or monthly. Then, count how many positive, negative, and neutral reviews appear in each time period. You might also calculate the percentage of positive reviews over time.
This time-series format is the foundation for your trend visualization.
4. Create Interactive Charts with Plotly
Use Plotly to plot your sentiment data. For example:
- A line chart showing positive and negative trends over weeks
- A stacked area chart displaying overall sentiment volume
- A pie chart for the latest month’s breakdown
These charts let viewers interact with the data—hovering to see exact numbers, filtering by time, or toggling categories.
5. Build a Dashboard with Streamlit
Now it’s time to bring it all together. Using Streamlit, you can create a simple dashboard layout that includes:
- Introductory text
- Interactive Plotly charts
- A date filter or dropdown menu for selecting product categories
You don’t need to write a single line of frontend code. Just organize your visuals and add widgets using plain Python, and Streamlit handles the rest.
Your finished app is a user-friendly dashboard that anyone on your team can use—right in their browser.
Tips for an Effective Sentiment Dashboard
Here are some best practices to make sure your dashboard is both useful and user-friendly:
- Keep it focused: Don’t overcrowd the dashboard. Choose the most meaningful charts and keep the layout clean.
- Use color intentionally: Assign consistent colors—like green for positive, red for negative—to make sentiment instantly recognizable.
- Add context: Include short explanations or tooltips so users know what they’re looking at.
- Make it interactive: Use filters, sliders, and tooltips to let users explore the data their way.
- Highlight key events: Annotate spikes or dips in sentiment with relevant business actions (e.g., “Product update launched”).
Final Thoughts
Creating a sentiment dashboard might sound technical, but with tools like Streamlit and Plotly, it’s accessible to anyone. Whether you’re a marketer wanting to monitor brand perception, or a product manager gauging customer reactions, visualizing sentiment trends can give you the clarity you need.
Want to learn how to build one for yourself?
👉 Register for our upcoming session: https://lu.ma/4p686lqe
We’ll walk through a real-world demo and show you how to turn feedback into interactive insights—no coding experience needed!
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