Learning Outcomes:
Understand the concept of Hashtag(s) analysis on TRAC.
Learn how to use Hashtag analysis to identify main themes in your dataset and inform your creative strategy.
Understand how Hashtags Analysis can help you gain deeper insights about your audience.
What are Hashtags?
Hashtags are words or phrases preceded by the '#' symbol that are used to categorize content on social media platforms such as X, Instagram and Facebook. Most social media conversations are organic and unstructured: hashtags help organize and categorize them, creating a sort of user-generated tagging, which helps observers discern patterns and easily find and follow content with specific themes.
On most social platforms, when a user includes a hashtag in their post, it becomes a clickable link that leads to a page displaying all the other posts that have used the same hashtag. This allows users to discover new content and connect with others who share their interests.
What insights can I uncover from Hashtags Analysis?
Hashtags can be used for a wide variety of purposes, from organizing events to promoting products, to expressing opinions on social or political issues. And being able to visualize hashtags separately from keywords is helpful given that hashtags are often more succinct. This gives you another lens to understand the conversation, sentiment and emotion around a particular topic. So whether you’re reporting on a campaign you carried out for a client, or trying to get a sense of how the conversation has evolved, hashtags will help you uncover some useful insights.
Similar to the Keywords, Entities and Topics sections on TRAC, you’ll be able to see Hashtag analysis in various charts, under Content Insights. Let’s take a look at each one of them in more detail.
Hashtags Treemap by Data Source
The Treemap visualisation provides insights into the channels where certain hashtags are used most frequently. The size of the tile represents the prevalence of that hashtag being used on a particular channel. It also helps to identify if certain hashtags are over-indexed or under-indexed on some data sources. For instance, the screenshot below shows that #crypto is a highly popular hashtag across all channels. However, the Treemap highlights that the hashtag over-indexes by +6.53% on X compared to other data sources, which is an interesting insight.
Hashtags Sentiment Word Cloud
When looking at hashtags displayed in a Sentiment Word Cloud, you can understand the most common hashtags in a search and the sentiment associated with those hashtags. The bigger the size of the hashtag, plus the more central it is in the graph, then the greater the number of posts and articles containing that hashtag.
Hashtags Emotions Word Cloud
When looking at hashtags displayed in an Emotions Word Cloud, you can understand the most common hashtags in a search and the emotions associated with those hashtags. The bigger the size of the hashtag, plus the more central it is in the graph, then the greater the number of posts and articles containing that hashtag.
Hashtag Segments
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.
Hashtags Stream
Analysing hashtags displayed in a Stream graph enables you to track how the discussion around particular themes evolves over time. This allows you to identify when a specific hashtags emerged, as well as when the conversation subsided and possibly resumed. By correlating this information with relevant media events, you can gain valuable insights into why certain hashtags were included in the discourse.
Hashtags Bundle
Sometimes known as a chord diagram, the hashtag Bundle chart is a graphical representation of the relationships between the different themes in a dataset. It's a great way to visualise the inter-relationships and flows between the hashtags as arcs or chords, that connect the hashtags. Each hashtags is represented as a segment around the perimeter of the circle, with the chords connecting the hashtags representing the degree of overlap, or connection between them. The bigger the segment around the perimeter of the circle is, then the more connections that hashtag has with other hashtags in the bundle chart.
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