Sentiment Analysis Dashboard

This article gives an overview of everything to know about Sentiment Analysis in Uberall

Last updated on January 31st, 2022

The Sentiment Analysis dashboard will provide you insights into what your customers are saying about your locations. Easily see if a topic is trending positively or negatively so that you know where to begin making changes. 

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The Sentiment Analysis dashboard is in Uberall's Analytics module.

  1. Start by clicking on Analytics on the side navigation bar
  2. When enabled, Sentiment Analysis will appear in the sub-list


At the top-right of the Sentiment Analysis dashboard are the following filters that you can utilize to adjust the data in the dashboard. 

  1. Accounts
  2. Location
  3. Directory
  4. Date (defaults to last 30 days)

Sentiment Dashboard Cards

Sentiment Score

The Sentiment score is a starting point to see how customers generally feel about your locations. This is on a scale of 0-100 and provides a summary of the overall sentiment of all reviews from the filtered locations. An easy way to think of the score is:

  • 0 - all negative reviews
  • 50 - all neutral (or an even number of negative and positive reviews)
  • 100 - all positive reviews

Scoring Formula

Uberall assigns each sentiment value a number of points:

  • Negative Sentiment is scored as 0 points
  • Neutral Sentiment is scored as 1 point
  • Positive Sentiment is scored as 2 points

The maximum possible grade would be the total pieces of content (e.g., reviews) or total theme mentions (e.g., food, facilities, etc.) multiplied by 2. So, the formula for calculating the grade is:

Grade = Total Points Scored / Maximum Possible Points

Let’s take a look at some examples to see how this would work.

Example 1

A location has three reviews that have been labeled with the following mentions of “Food”:

  • Review 1 = Positive (2 points)
  • Review 2 = Neutral (1 point)
  • Review 3 = Negative (0 points)

Total Points Earned = 3 points

Each review has the potential to earn 2 points (positive sentiment). This means that the maximum possible score for this example under the Food theme would be 6 points.

Based on the total points earned for the three reviews, the “Food” grade for this location would be:

3 (total points earned) / 6 (Maximum Possible Points) = .50 or 50%.

Example 2

Let’s look at another example that is calculating a summary sentiment grade across multiple locations.

Let’s assume that you have 100 locations and, across those 100 locations, you’ve received 1,000 reviews of varying sentiment. In this case, the Maximum Possible Points would be 2,000 (1,000 reviews x 2 points possible per review).

Let’s assume that the actual positive/neutral/negative points scored across those 1,000 reviews = 1,652. In this case, the summary sentiment for this group of locations would be:

1,652 / 2,000 = .826 or 83%.

Keyword Cloud

By clicking on View Details under the score, you'll see a keyword cloud containing the most frequently used words in your reviews, as well as a color corresponding to the sentiment of those reviews.

  • Green indicates positive sentiment
  • Yellow indicates neutral sentiment
  • Red indicates negative sentiment

Total Mentions

The total mentions will help you keep track of your positive, neutral and negative review count and trends. Start to see negative trending up and it may be time to look at the reviews to see what customers are saying 

These sections will categorize the sentiment themes extracted from your reviews. Each category will receive its own score and trending indicator

Sentiment Location Table

Further down in the Sentiment Analysis Dashboard, we will see the sentiment information outlined for each location. The locations can be filtered using the page filters at the top of the dashboard.

Score filtering

Using the dropdown on the table, you can quickly segment locations by their score thresholds. This will display the locations for the selected score range. Quickly find locations with negative sentiment and work to remedy the customer experience.

Column Visibility

The visible themes in the table can be adjusted by clicking on the columns button. Add relevant themes or remove non-relevant themes to tailor the experience. Additionally, reorder the themes in the table to see the most relevant information first

Location Details

Each row of data includes the following info for each location:

  1. Ranking of the location based on the sorting criteria of the table
  2. Number of reviews received
  3. Overall sentiment score for the location
  4. Trending indicator
  5. Average star rating for the location
  6. Each theme and the sentiment score graded. (note if no reviews were found for the given theme, this will be blank)

Review Panel (second release)

Clicking on the score in the sentiment column will reveal a panel that displays all reviews that contribute to that score

Filter Options

Reviews in the panel can be filtered by theme or sentiment (positive, neutral, negative)

Review Cards

Each review in the review panel will display the following info:

  • Directory of origin
  • Star rating of the review
  • Review content
  • Overall sentiment of the review
  • Review author
  • Listing that the review appears on

*In a future release, users will be able to select reviews and share them via email. 


What languages are currently supported?

Currently Sentiment Analysis can only be performed on reviews in English, however supporting German, French and Spanish are near-term items in the roadmap


Why are some reviews missing from the dashboard?

Not all reviews can be evaluated for sentiment. Reviews must meet the following criteria in order to be evaluated

- Long enough text (character count varies)
- Enough text without special characters (reviews of just emojis cannot be evaluated)


How does sentiment get determined?

Reviews can have two different types of sentiment that is determined by our machine learning algorithm

Overall Sentiment is an analysis of the overall review text and whether it is positive, neutral or negative. All eligible reviews will at least have an overall sentiment determined

Sentiment Themes are concepts extracted from different parts of the review. Each theme present is then scored for sentiment. For example, a single review may contain a positive note about the food, and a negative note about the service. This would result in the Food and Service themes being identified as positive and negative respectively


How does the Sentiment Score get calculated?

The sentiment score is an aggregate of all the relevant reviews. Each review or theme will get "points" depending on the sentiment determined:

Positive sentiment - 2 points
Neutral sentiment - 1  point
Negative sentiment - 0 points

The score is a simple ratio of the total points received, divided by the total points that could have been attained. An easy conversion works like this:

0 - all negative
50 - all neutral (or equally negative and positive)
100 - all positive


Does sentiment analyze new reviews only or also older reviews?

All eligible reviews (new and old) will be analyzed for sentiment


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