Sentiment (Discover)

About Sentiment

Sentiment is an enrichment provided to you in all of your XM Discover data sources. Sentiment measures how positive or negative an individual comment is. Sentiment is calculated at a sentence level on a -5 to 5 scale, and can be divided into either 3 or 5 scale segments: Very Negative, Negative, Neutral, Positive, and Very Positive.

Qtip: When exploring customer feedback in document explorer or a feedback widget, you can highlight sentiment-related data. Sort or filter documents by sentiment, or enable sentiment badges that appear next to each sentence.

How Sentiment Is Calculated

XM Discover analyzes the sentiment of a sentence based on the tone of the words and phrases within the sentence.

• Words: Designer comes with thousands of words that are flagged as positive or negative, based on our implementation experience. You can either use default tunings or adjust them to better suit your data with tuning.
• Phrases: In addition to word-level sentiment, Designer also recognizes sentiment modifiers and exception rules that cover most well-known sentiment-changing linguistic patterns for all supported languages. You can manage default rules or create custom ones.
• Machine Learning Sentiment: Discover uses machine learning to evaluate the positivity/negativity of text and assign sentiment labels to sentences across all supported languages. If it is enabled, this kind of sentiment replaces the rules-based approaches for brands.

Sentiment Scale

When adding sentiment to widgets, you can often choose between a 3 and 5 point scale. The 3 point scale only includes negative, neutral, and positive.

Using Sentiment Data

Sentiment can be used across XM Discover to build informative dashboards. Display sentiment to your stakeholders, filter data, and even build unique custom sentiment metrics to meet your organization’s needs.

When paired with text analytics, sentiment analysis can be beneficial in many ways:

• Prioritize customer feedback and handle large volumes of it consistently and accurately.
• Discover your customers’ opinion on everything from your products and services to your location, your advertisements, or even your competitors.
• Understand what customers like and dislike about you and your brand.
• Analyze customer emotional feedback from social media, your website, your call center representatives, or any other source that contains useful business information.
• Keep up with changes in public opinion toward any aspect of your business.
• Identify where you need to make product improvements, train sales or customer care representatives, or create new marketing campaigns resulting from peaks or valleys in sentiment scores.

Grouping Widget Data by Sentiment

When creating widgets in Studio, you can group data by sentiment.  When you group data by sentiment, it’s important to keep in mind the following difference between sentence-level and record-level sentiment in Studio:

• While each sentence can only have 1 sentiment score, a document has as many sentiment scores as there are sentences in it.
• That means that if a document contains 1 positive and 1 negative sentence, it is considered both a positive and a negative document.
• This is why when data is grouped by sentiment, the total count is usually less than the sum of all records in each band. See the widget below.

Example: If you add up the volume of each segment ( 1425 + 1395 + 930 + 729 + 243), you’ll notice this is higher than the total volume given, 1663. This is because there are 1663 documents, but 4722 sentences with sentiment evaluated.

When data is grouped by sentiment, the colors in the widget will match the defaults set for the sentiment bands. Color may not match these settings if a different field is used to group data.

Machine Learning Based Sentiment

Machine learning based sentiment assigns labels ranging from “Very Negative” to “Very Positive” to sentences.

• Name: Sentiment
• System Name: XM_sentiment
• Type: Numeric
• Scale: -2 to 2
  Qtip: If a sentence does not contain sentiment bearing words, it will be given the value “N/A”. The sentiment will be labeled “Neutral” when coloring by sentiment in an aggregate widget if all other sentences in the data point are also “N/A”.
• Granularity: Sentence
• Feedback Type: All
• Supported Languages: All

Rules Based Sentiment

Here’s some information on the Sentiment attribute in Designer:

• Name: CB Degree Sentiment Index
• System Name: _degreesentimentindex
• Type: Numeric
• Scale: -5 to 5
• Granularity: Sentence
• Feedback Type: All
• Supported Languages: Talk to your Discover Account Representative.