Smart Theme Explorer v/s Topic Cluster
Updated
Topic Cluster
For generating topic clusters, we take a large sample of messages (randomly selected after applying the given dashboard/widget filters) and perform data hygiene steps like stemming and removal of stop words from these messages. We then identify phrases frequently occurring in the messages (we have an underlying text analysis engine to do that) and then cluster the messages into groups defined by these phrases. As the sample of messages generated is random, hence the topic cluster might seem different at different moments.
1st Tier/Internal – The most occurring phrase in the data
2nd Tier/Internal – The most occurring phrase in the individual sections of the 1st tier
Smart Theme Explorer
Smart Theme Explorer is a research tool that enables users to quickly understand the underlying themes of conversation under a Topic or any data-fetching listening entity, thereby helping them cut through the clutter of unstructured data.
It is a free tool for all Sprinklr Insights users and must not be compared with specialized tools like Product Insights which are supervised, verticalized, and highly specific.
Product scope
Available for limited languages currently.
Smart Theme Explorer can work on all data fetching listening entities like Topic, Topic Groups, Account, Account Groups, Brands, Business Locations, Products, and first-party data as well.
Cluster sentiment is derived from the message-level sentiments.
The maximum number of levels up to which you can navigate is 5. It might be possible that no clusters are formed after a particular level due to insufficient data.
Difference between Smart Theme Explorer and Topic Cluster
Parameter | Smart Theme Exploere | Topic Cluster |
Sampling |
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Inappropriate Content Filtering | Mentions containing inappropriate phrases, keywords, profanity are not counted towards clustering | No Content-based filtering for inappropriate data. |
Data Hygiene | Stop words are removed | Stemming of phrases |
Number of Clusters | All possible clusters are present and shown and can be seen via pagination or list view. | Limited and top occurring phrases are shown only. |
Volume Representation | Volumes are represented by the size (radius) of the cluster. | The size of a cluster does not represent the volume of that cluster. |
Phrase Identification | AI-based but more advanced. Identifies subjects and attributes at a sentence level, takes into account nouns, adjectives, verbs, adverbs, etc. | AI-Based (NLP) |
Pairing and Correlation of Clusters |
| Phrases are clustered solely on the basis of volumes of mentions for the phrase. |
Level of Clustering | Up to 5 levels | Up to 2 levels |
Additional Capabilities |
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Sentiment | The sentiment of clusters is shown in the UI | The sentiment of clusters is not available. |