4. The non-transitory computer storage medium of claim 1 , wherein the user selection specifies the data is sampled from all users or popular users.
1. A non-transitory computer storage medium storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations comprising: sampling data, via a social engine, from one or more social media streams, in accordance with a user selection received via a user device; assigning part-of-speech (POS) tags to text in the data; applying natural language processing, by a trending topic tool, to extract candidate topics from the data using a first rule comprising: identifying a sequence of a plurality of the assigned POS tags, wherein each POS tag of the sequence is selected from a group consisting of at least one of a proper noun tag, a plural proper noun tag, or a cardinal number tag; defining topic boundaries based on the identified sequence; and extracting a portion of the text corresponding to the topic boundaries as one of the candidate topics; ranking the candidate topics, by the trending topic tool, with a relevance score that quantifies relative importance of each candidate topic to determine trending topics; classifying, by the trending topic tool, the trending topics into categories; grouping the candidate topics into topic clusters of semantically-similar topics, by the trending topic tool, and transmitting the classified and clustered trending topics for display on the user device.