Learning Outcomes
Gain a better understanding of the importance of Topics within the context of Content Insights.
Learn how to use the Topics Treemap by Data Source, Topics Sentiment Word Cloud, Topics Emotion Word Cloud, Topics Stream and Topics Bundle to analyse and identify trends in your dataset.
What are Topics in Content Insights?
Topics refer to the most commonly spoken about subjects within your dataset. By analysing the topics within your search, you can gain insights into the trends and patterns of conversation and identify relationships between different data sources.
You can learn more about how we calculate Topics here.
How to Analyse Topics Using Content Insights
Topics Treemap by Data Source
The Topics Treemap by Data Source displays your dataset's most frequently discussed topics. Each topic is represented as a tile, with the size of the tile indicating the frequency or importance of the topic. The treemap is also segmented based on the data sources present within your search and can be used to identify patterns and relationships between topics and data sources.
📈 Example: In the below analysis of a conversation relating to the coffee industry, the presence of X and Reddit on the treemap suggests that these platforms are the primary sources for discussing coffee.
Additionally, if the keywords "drinks", "non-alcoholic drinks", "food industry" and "hot drinks" frequently appear together, it may indicate that they are related and should be considered together in content marketing strategies or SEO optimisation.
There are two key takeaways that you can get from this treemap:
The presence of X and Reddit on the treemap suggests that these are the primary platforms for discussing coffee, as evidenced by the overwhelming amount of discussion across these two channels.
The keywords drinks, alcoholic drinks, cocktails with gin, and mixed drinks frequently appear together, it might indicate that they are related and should be considered together in content marketing strategies or SEO optimisation
Topics Sentiment Word Cloud
The Topics Sentiment Word Cloud is a visual representation of text data that shows the frequency and importance of each topic in your dataset, whilst indicating the sentiment attributed to each. This can help you understand the most prevalent topic in a conversation and the overall sentiment of these topics within the conversation.
📈 Example: In the example below, the topics of "food watchlist", "hot drinks" and "food and drink preparation" feature prominently in the search.
In the example below you can see that the topics of food watchlist, hot drinks and food and drink preparation feature prominently within this search.
Topics Emotion Word Cloud
The Topics Emotion Word Cloud is similar to the Sentiment Word Cloud but shows the emotional tone attached to each topic. This provides deeper insights beyond the automated sentiment score of positive, negative, and neutral, and can help you understand the emotional context of conversations and topics being mentioned.
📈 Example: In the image below, the keyword "crypto" is most commonly mentioned in a joyful context, whereas the keywords "ridiculous" and "wtf" are mentioned with undertones of anger.
📝 Note: The same topic may be detected multiple times in the word cloud, but based on the emotional analysis of the content the topic has been extracted from, it will have a different emotion score.
Topic Segments
"Topic Segments" cluster topics that are being commonly used together in posts within your search. These segments can help to provide content recommendations, such as direction on creating content centred around the primary subject areas recognised in the visual. By using segments, you can segment and cluster the topics being commonly used together in your search.
Topics Stream
The Topics Stream is used to analyse the top ten topics in a conversation over a given period of time. This can help you identify trends and patterns around the topics becoming more or less prevalent within the conversation.
Topics Bundle
The Topics Bundle helps you understand the relationships between specific topics within your dataset. By identifying the frequency and proximity of topics that appear together, you can visualise the connections between them.
💡 Top Tip: Click on a particular topic on this visual to see the connections between other topics. This can be used to identify which topics are being discussed together and inform your campaigns and strategies around certain topics for the greatest impact.
We hope you enjoyed reading this article! 📚
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