Truly understanding your community is a key element when it comes to crafting a content strategy tailored to your audience’s needs. More specifically, it’s important to quickly be able to know the sentiment of your audience’s posts and comments, so that you can not only improve your social media strategy – but also prevent any negative waves from growing into something larger. After all, it’s better to respond to smaller issues that can still be dealt with on social media quickly, as opposed to dealing with escalating problems that could over time harm the profile or the overall brand.
With Sentiment Analysis in Suite, you can quickly and easily set up manual sentiment analysis – as well as automate your sentiment analysis with the click of a button. Streamlining your sentiment analysis efforts has never been easier!
How does Sentiment Analysis work?
Sentiment Analysis is based on four values – Positive, Negative, Neutral, and No Sentiment. These values are illustrated by specific examples from real profiles below:
- My love and respect for Prince Charles is unwavering.
- God bless the people of California and give them strength to survive.
- This is the worst phone company on the planet.
- Too many residents are criticizing firefighters for not saving their homes.
- No Sentiment Applied (default value)
- Very sad… (While this seems like it could be negative, it's too short for sentiment to be truly detected.)
Sentiment Analysis is available for Facebook, Twitter, and Instagram, and can be applied to:
- A comment on any post
- A reply on any post
- A Facebook user post
- A direct conversation - sentiment is applied to the entire conversation, not to a particular message
- Twitter mentions
- Twitter replies
- A comment on any post (owned pages only)
Note: Due to API restrictions, sentiment analysis can only be applied to Instagram comments for owned pages. For this reason, it isn’t possible to apply sentiment to comments on monitored profiles on Instagram.
Sentiment cannot be applied to:
- Facebook Page Posts, Sent Tweets, Instagram Posts
- Admin Comments (comments that were created by the profile that created the post)
Get a Clear Overview of Sentiment with Aggregations
In order to have a complete overview of the sentiment of posts, sentiment is aggregated on Facebook Page Posts, User Posts, Sent Tweets, Twitter Mentions, and Instagram Posts.
The Radiator indicator shows the ratio of positive to negative comments and replies, allowing you to get a quick and comprehensive snapshot of your fans’ sentiment. Please note that the sentiment aggregation on posts does not contain the sentiment value of the actual post.
Moreover, the comments part of posts includes a pie chart that shows the ratio of positive, negative, neutral, admin, and ‘no sentiment’ comments. In this case, you can get a more detailed overview of the sentiment of your fans’ comments, allowing you to drill down into the latter and understand how to react accordingly.
The Radiator indicator showing the breakdown of 4 positive vs 1 negative comments and replies on a post
The pie chart indicator showing the breakdown of the ratio of positive, negative, neutral, admin, and ‘no sentiment’ comments
Comment Sentiment Summary section, which allows users to view the sentiment of all comments on one page as well as manually change the sentiment of comments with ease
In addition to sentiment analysis being part of Analytics in Suite, it’s also possible to monitor and analyze sentiment with the help of two Dashboard widgets: Sentiment of Comments and Sentiment of Comments & User Posts.
The Pie Chart visualization can be used to get an overview of the sentiment of Comments and User Posts on a specific profile. The Comparison visualization, on the other hand, can be used to compare the sentiment across profiles or labels.
Automate your Sentiment Analysis With Ease in Suite
In order to streamline sentiment analysis even further, it is also possible to leverage automated sentiment analysis. With automated sentiment analysis, you can let Suite do the work for you, allowing you to save time and be able to recognize the sentiment of posts quickly. This means that no red flags will go unnoticed – and you will be able to react to comments and queries in an efficient way.
Automated sentiment is available for Comments, Tweets, Mentions, and User Posts. It is currently available for the English language and will soon be available for Portuguese and Spanish as well.
Want to get started with automated sentiment? Great! Setting it up is quick and easy. Users can turn it on by going to Settings - Task Automation - Sentiment. Automated Sentiment Analysis can also be turned on for specific profiles only.
Tip: Don’t forget that the Global Labeling permission is needed to access the Sentiment section.
Let Automated Sentiment Analysis do all the heavy lifting
Automated Sentiment first analyzes all Comments, and, if English is detected, it applies a sentiment based on our advanced sentiment library. When the sentiment is recognized automatically, the letter A is added next to the comment.
And here’s how it works in practice. Turning on automated sentiment simply reveals or hides the sentiment values that are stored in our database. This means that it's also possible to show past automated sentiment – from September 2018 onwards. If a comment doesn’t have a sentiment assigned, this can be due to the fact that it’s not in the supported language (English) or because it’s too short – or because our engine doesn’t recognize the sentiment.
Automated Sentiment can be found in the same place as manual sentiment. What’s more, you can always manually change all automated sentiment – so you can rest easy knowing that you’ll always have the final say. It should also be noted that manual sentiment has a higher priority than automated sentiment, as users can change the automatically assigned sentiments in the comment detail.
Whether you’d like to try out using manual sentiment or automated (or both, for the best experience!), rest assured that sentiment analysis in Suite can help you understand your fanbase, catch possible mishaps before they turn into big issues – and ultimately always make your audiences happy. Streamlining community management has never been easier!