If you're using TRAC's Content Insights subpage to analyse social data, you'll likely be interested in understanding the most commonly used entities within your dataset. Thankfully, TRAC provides several visualisations to help you do just that.

The first visualisation you'll likely encounter is the "Entity Treemap by Data Source". This visualisation provides a graphical representation of the most common entities in your dataset. Each entity is represented by a rectangle, with the size of the rectangle proportional to the frequency or importance of the entity. The rectangles are segmented based on the data sources present within your search. This visualisation can be particularly useful for identifying which entity are most prevalent across different data sources.

A word cloud is a graphical representation of textual data, where the size of each entity signifies its frequency or significance within the text, and the colour of the entity denotes the sentiment associated with it.

By examining the dimensions of these entities in the word cloud, you can discern that posts with positive and neutral mentions appear more frequently than those with negative mentions. This offers valuable insights into the overall sentiment associated with the entity under investigation.

Another useful visualisation is the "Entity Emotion Word Cloud". This word cloud functions similarly to a traditional word cloud, with the size of each entity corresponding to its frequency or importance within the text. However, the colouration of the entity indicates the emotional tone attached to it. This can be helpful for understanding the emotional context of the most commonly mentioned entities within your dataset.

"Entity Segments" cluster entites 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 the entities being commonly used together in your search and analyse them.

The "Entity Stream" is another visualisation that can be helpful for understanding the usage of specific entities over a given period of time. This visualisation displays a graph of entities usage, allowing you to identify trends and patterns in entity usage over time.

Finally, the "Entity Bundle" is a visualisation that helps you understand the relationships between specific entities within your dataset. This visualisation works by identifying the frequency and proximity of entities that appear together and visualising these connections. By clicking on a particular entity, you can see the connections between that entity and other entities within your dataset.

By using these visualisations, you can gain a deeper understanding of the most commonly used entities within your dataset and how they relate to each other. This information can be particularly useful for identifying trends and patterns in entity usage, as well as understanding the emotional tone of conversations around specific entities. So next time you're analysing social data with TRAC's Content Insights, make sure to take advantage of these powerful entity visualisations.