Unlock Insights with AI-coded Sentiment Analysis Using Google Sheets
Table of Contents
- Introduction
- Background
- Using AI for Sentiment Analysis
- Creating a Pivot Table
- Analyzing Topics and Sentiments
- Adding Session Information
- Assigning Scores to Sentiments
- Calculating Overall Score
- Date Grouping in Pivot Tables
- Visualizing Trends with Charts
- Conclusion
Introduction
In this article, we will explore how to analyze feedback data using spreadsheet tools. We will discuss the process of coding comments with sentiment analysis using AI and delve into the topics and sentiments that appear frequently. We will also look at how to drill down into individual comments and connect them to session information. Additionally, we will learn how to assign scores to sentiments and calculate an overall score. Finally, we will explore date grouping in pivot tables and visualize trends using charts. By the end of this article, you will have a comprehensive understanding of how to analyze feedback data effectively and gain valuable insights.
Background
Before we dive into the analysis process, let's first understand the background of the data. The spreadsheet contains comments that were feedback to workshops along with the corresponding dates. The goal is to analyze these comments using AI to gain insights into the topics and sentiments expressed. The initial coding was done using sentiment analysis, categorizing the comments as negative, positive, or neutral. However, further exploration is required to identify recurring topics and sentiments and understand the overall sentiment trends.
Using AI for Sentiment Analysis
To begin the analysis process, we will utilize AI to code the comments and determine their sentiments. By using AI, we can perform sentiment analysis and categorize the comments as negative, positive, or neutral. This process may require breaking down the comments into smaller pieces to ensure accurate coding. Once the coding is complete, we can proceed to explore the data using spreadsheet tools and gain a better understanding of the topics and sentiments present.
Creating a Pivot Table
One of the most useful tools for analyzing data in spreadsheets is a pivot table. It allows us to summarize and aggregate data based on different criteria. To create a pivot table, we need to select the original data and go to the "Insert" tab. From there, we choose "Pivot Table" and select the location where we want to place the pivot table. Once the pivot table is created, we can configure the rows, columns, and values to organize the data effectively.
Analyzing Topics and Sentiments
In the pivot table, we can analyze the topics and sentiments expressed in the comments. By selecting the topic as the rows and counting the sentiments as the values, we can determine how many times each topic appears and the distribution of sentiments for each topic. This provides us with an overview of the topics discussed and the overall sentiments expressed. We can identify recurring topics and explore the sentiments associated with them.
Adding Session Information
To gain more insights into the comments, we can connect them to session information. Although the original data may not include session names, we can use a formula called VLOOKUP to retrieve the session names from another sheet. By matching the comments to their respective sessions, we can analyze the feedback in the context of the specific sessions. This additional information allows us to identify areas for improvement and make informed decisions based on the feedback received.
Assigning Scores to Sentiments
In addition to categorizing sentiments as negative, positive, or neutral, we can also assign scores to provide a quantitative measure of sentiment. By assigning scores such as -1 for negative sentiments, +1 for positive sentiments, and 0 for neutral sentiments, we can evaluate the overall sentiment score. This scoring system allows for a more nuanced analysis of sentiments and provides a numerical value for sentiment evaluation.
Calculating Overall Score
To calculate the overall score based on the assigned sentiment scores, we can use spreadsheet functions. By summing up the scores and dividing them by the total number of comments, we can obtain the average score. This average score represents the overall sentiment of the feedback received. Analyzing the overall score helps us gauge the general sentiment towards the workshops and identify areas of strength or areas that require improvement.
Date Grouping in Pivot Tables
To gain a better understanding of how sentiments and scores evolve over time, we can utilize date grouping in pivot tables. By grouping the comments by year and month, we can analyze the trends and fluctuations in sentiment and scores over different time periods. This grouping allows for a more comprehensive analysis of the feedback data and helps identify patterns or seasonal variations.
Visualizing Trends with Charts
To visualize the trends in sentiment scores over time, we can create charts based on the data from the pivot table. By selecting the relevant data and using the charting tools in the spreadsheet software, we can create line charts or other suitable visualizations. These charts provide a graphical representation of the sentiment trends, making it easier to interpret and communicate the insights derived from the analysis.
Conclusion
Analyzing feedback data using spreadsheet tools provides valuable insights into the sentiment and topics discussed. By leveraging AI for sentiment analysis, utilizing pivot tables for summarizing data, and connecting comments to session information, we can gain a comprehensive understanding of the feedback received. The process of assigning scores, calculating overall sentiment, and grouping data by date enhances the analysis further. Visualizing trends with charts allows for effective communication of the insights derived. By following the steps outlined in this article, you can analyze feedback data efficiently and make data-driven decisions to improve workshops or any other project based on the feedback received.
