Machine-learning system for servicing queries for digital content

A method comprising:

• receiving, by a content-extraction system and from a client device, a query regarding an entity, the content-extraction system positioned remotely from the client device and between the client device and a search computing device that is configured to search a digital dataset based on keywords, wherein the query includes a request for documents with a certain sentiment regarding the entity;
• creating, by the content-extraction system, a result set of digital content responsive to the query, wherein creating the result set of digital content comprises:
• obtaining, from the search computing device, a set of digital content, each digital content item in the set of digital content including one or more keywords identified from the query,
• generating, based on one or more machine-learning models, a reduced set of digital content by removing non-core content and duplicates from the set of digital content,
• executing, a content-attribute machine-learning model for each digital content item in the reduced set of digital content to determine a sentiment score based on a respective portion of each digital content item in the reduced set of digital content, and
• selecting, as the result set of digital content, a subset of digital content from the reduced set of digital content, wherein the subset of digital content is selected based on the sentiment score determined for each digital content item in the reduced set of digital content;
• and
• transmitting, by the content-extraction system, the result set of digital content to the client device.

A non-transitory computer-readable medium having program code stored thereon, wherein the program code, when executed by one or more processing devices of a filtering system, configures the filtering system to perform operations comprising:

• receiving, from a client device, a query regarding an entity, wherein the filtering system positioned remotely from the client device and between the client device and a search computing device that is configured to search a digital dataset based on keywords and wherein the query includes a request for documents with a certain sentiment regarding the entity;
• creating a result set of digital content responsive to the query, wherein creating the result set of digital content comprises:
• obtaining, from the search computing device, a set of digital content, each digital content item in the set of digital content including one or more keywords identified from the query,
• generating, based on one or more machine-learning models, a reduced set of digital content by removing non-core content and duplicates from the set of digital content,
• executing a content-attribute machine-learning model for each digital content item in the reduced set of digital content to determine a sentiment score based on a respective portion of each digital content item in the reduced set of digital content, and
• selecting, as the result set of digital content, a subset of digital content from the reduced set of digital content, wherein the subset of digital content is selected based on the sentiment score determined for each digital content item in the reduced set of digital content;
• and
• transmitting to the client device the result set of digital content.