Pulsar's unique network visualisation capabilities and innovative segmentation algorithm have always been some of our strongest USPs. Our Segments feature can transform any conversation or data point into a network of distinct segments, based on their unique characteristics and properties. These segments can represent a variety of data points such as authors, images, entities, topics, or keywords. With Pulsar's clustering algorithm, you can easily identify and group these data points into relevant segments to help shape and inform your creative or audience strategy.

Segments clustering allows you to quickly and easily identify data points that are frequently associated or discussed together within a conversation. These data points can include groups of authors based on their bios, groups of keywords, entities, hashtags or topics, and groups of images based on their extracted concepts. By analysing the co-occurrence of these variables, Segments can help you gain valuable insights to inform your creative and content planning. For instance, you can use Segments to plan your content around the specific topic areas identified, or tailor your content to reach specific groups of people based on their bios.

Each node (circle) in the Segments graph represents either the following:

The size of each node is a combination of the number of connections plus the volume of occurrences for that node. The nodes are coloured and clustered into distinct clusters (up to 5) and the name of each cluster is determined by the nodes that have the highest number of connections and occurrences. The clustering algorithm we use is called Page Rank, which helps us determine the relevance and importance of each node within a given segment. To visualise the graph, we use a force directed layout algorithm. This means that linked nodes attract each other and are closer together, and non-linked nodes do not and are much further apart.

Segments can be found within Audience Insights and Content Insights, under the following sections:

and each segmented data point is telling a unique story about what people are discussing, the type of content and media being shared, and the groups of people involved in that conversation.

You will find the Top Bio Segments in the Audience Insights > Demographics section of your TRAC search. You can use this graph to identify the main groups of people involved in the conversation, based on how they describe themselves in their bios.

When looking at Hashtags displayed in a Segments or Network chart, you can start to identify groups of hashtags that tend to be associated or discussed together in the same conversation. This can be useful to help understand how specific hashtags are closely related. Related hashtags are grouped together into distinct segments, and the clustering algorithm we apply determines the relevance and importance of each hashtag within a given segment, helping you uncover the dominant themes in a dataset.

When looking at Keywords displayed in a Segments or Network chart, you can start to identify groups of terms that tend to be associated or discussed together in the same conversation. This can be useful to help understand how specific keywords are closely related. Related keywords are grouped together into distinct segments, and the clustering algorithm we apply determines the relevance and importance of each keyword within a given segment, helping you uncover the dominant themes in a dataset.

When looking at Entities displayed in a segments or network chart, you can start to identify groups of people, or organisations that tend to be associated or discussed together in the same conversation. This can be useful to help understand how your brand or client is associated with certain organisations or individuals. Related entities are grouped together into distinct segments, and the clustering algorithm we apply determines the relevance and importance of each person or organisation within a given segment, helping you uncover the dominant people or organisations in a dataset.

Lastly, when looking at Topics displayed in a Segments or Network chart, you can start to identify groups of topics that tend to be associated or discussed together in the same conversation. This can be useful to help understand how specific topics are closely related. Related topics are grouped together into distinct segments, and the clustering algorithm we apply determines the relevance and importance of each topic within a given segment, helping you uncover the dominant themes in a dataset.

In the Content section, we surface the top image concepts, segmented and organised into a network. The chart displays related images grouped together into distinct segments. By using this chart, you can distinguish different images that are associated with your brand, campaign, or a specific subject. Our clustering algorithm analyses each image segment and determines the relevance and importance of each image within it helping you to uncover the dominant and most important visual themes present in a given dataset.