Listening Sentiment

This feature is only available for Social Listening customers.

Sentiment analysis is a valuable tool for understanding how your audience is feeling about a given topic. However, measuring audience sentiment is a nuanced endeavor and often requires that brands apply their unique context and perspective to ensure an accurate assessment. Especially because sentiment ratings apply across both the Smart Inbox and Social Listening. 

For example, if a gaming publisher was listening for messages around a game their company produces called “War Zone,” they might find their sentiment results to be overwhelmingly negative because the term “war zone” is inherently negative. This can lead to skewed results and an inaccurate analysis on what the sentiment of the conversation on social actually is. Sometimes, sentiment analysis can be unintentionally inaccurate. 

The good news? You can use Sentiment Reclassification and a Sentiment Ruleset when creating your Listening Topics to help you increase the accuracy of sentiment.

 

Sentiment Reclassification

With Sentiment Reclassification, you can reclassify the sentiment rating that was applied to a message. The second, Sentiment Rulesets, helps with the “war zone” example above, by changing how Sprout’s sentiment classifier interprets words or phrases. 

In the example above, you could make “war zone” a neutral term since it is tied to a name of a game.  By changing the rating on individual messages or words and phrases, you can improve the sentiment accuracy and improve the ratings the algorithm applies to messages.

Sentiment reclassification is great for your Brand Health or custom Listening Topics that are smaller and don’t contain thousands of messages. You can quickly update the sentiment on a message-by-message basis.

Reclassifying message sentiment

To change the sentiment on a message:

  1. Navigate to your Topic Insights.
  2. Open the Messages tab.
  3. Select the Sentiment dropdown menu for the message you wish to reclassify.
  4. Select Positive, Neutral or Negative.
    listening_sentiment_reclassify.png

If you want to reclassify the sentiment of more than one message at once, you can select multiple messages. 

To reclassify the sentiment of more than one message:

  1. Select the messages you want to reclassify.
  2. Click the sentiment icon Screen_Shot_2023-01-11_at_5.24.46_PM.png.
  3. Select Positive, Neutral, Negative or Unclassified.

You can reclassify all messages (up to 1000) by clicking the checkbox at the top of the Messages window.

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It may take up to a minute for message sentiment changes to take  effect.

bulk_sentiment_reclassification.gif

You can also reclassify more than one message at once from the Message Explorer. To reclassify messages from the Message Explorer:

  1. Select the messages you want to reclassify from the Message Explorer window.
  2. Click the sentiment icon Screen_Shot_2023-01-11_at_5.24.46_PM.png.
  3. Select Positive, Neutral, Negative or Unclassified.

message_explorer__sentiment_reclassification.gif

You can reclassify all messages (up to 1000) by clicking the checkbox at the top of the Message Explorer.

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While Sentiment Reclassification is a great way to change sentiment on individual messages, a Sentiment Ruleset lets you decide how the sentiment classifier interprets and classifies specific keywords. A ruleset helps guide the sentiment classifier to make a more informed decision on how to treat words in a message. 

If a message is fairly straightforward, the message will likely get classified per your ruleset. For example, “I have back pain.”

The word “pain” in that message is interpreted as negative, so the overall message is negative. If you added a rule to make “pain” interpreted as neutral, the message rating likely becomes neutral. 

It’s important to know that sometimes the rest of a message can influence the overall sentiment classification. For example if the message said, “I have bad back pain. These new pills are awful and don’t help.” The message is interpreted as negative. Whereas, “I have bad back pain. These new pills I got are great.” This message is interpreted as positive.

In both of the situations, other keywords and phrases influenced the classification of the message beyond the rule. But, in either case, you’re ensuring the word “pain” remains neutral and leaving the rest of the message context to determine the true sentiment.

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