Systems and methods for providing recommendation to modify deficient content item
Systems and methods are disclosed herein for providing a recommendation to modify deficient a deficient content item. A plurality of content items associated with a topic is retrieved. Each of the content items includes a plurality of portions each associated with a respective sub-topic. A rating for each sub-topic of the content items is calculated, and a minimum viable subset of the sub-topics is identified based on the calculated ratings. A new content item associated with the topic is accessed. A plurality of portions of the new content item is identified and a sub-topic for each identified portion is determined. An omitted sub-topic of the minimum viable subset of the sub-topics that is not included in the sub-topics of the new content item is identified, and the system interrupts upload of the new content and recommends modifying the new content item to include a portion with the omitted sub-topic.
1. A method, comprising:
receiving, by a computing device, a first request to post a first content item about a topic, wherein the computing device makes posts of content items available to a plurality of devices via a network;
accessing a database of the computing device that stores a plurality of second content items directed to the topic;
analyzing, using a machine learning model, the plurality of second content items that are directed to the topic to determine a plurality of required sub-topics;
determining the first content item is missing a sub-topic of the plurality of required sub-topics;
based at least in part on determining the first content item is missing the required sub-topic, rejecting the first request to post the first content item;
receiving a second request to post a modified first content item; and
posting the modified first content item, based at least in part on determining that the modified first content item includes the missing required sub-topic.
2. The method of claim 1 , wherein analyzing the plurality of second content items comprises parsing a plurality of online reviews.
3. The method of claim 2 , wherein the first content item is an online review.
4. The method of claim 1 , wherein the machine learning model comprises a neural net.
5. The method of claim 1 , wherein the plurality of required sub-topics are included in a majority of the plurality of second content items.
6. The method of claim 1 , wherein the plurality of required sub-topics are determined using a subset of the plurality of second content items having a rating above a threshold.
7. The method of claim 1 , wherein:
analyzing the plurality of second content items comprises identifying keywords in each of the plurality of second content items; and
determining the first content item is missing a sub-topic of the plurality of required sub-topics comprises determining the first content item is missing a keyword of the identified keywords.
8. The method of claim 1 , wherein:
the first request is to post the first content item to an online review portal; and
the computing device makes posts of content items available to a plurality of devices via the online review portal.
9. The method of claim 8 , wherein the plurality of second content items are posts to the online review portal.
10. The method of claim 1 , further comprising transmitting for display a recommendation to modify the first content item to include the missing required sub-topic.
11. A system, comprising:
transceiver circuitry configured to:
receive a first request to post a first content item about a topic, wherein the system makes posts of content items available to a plurality of devices via a network; and
control circuitry configured to:
access a database of the system that stores a plurality of second content items directed to the topic;
analyze, using a machine learning model, the plurality of second content items that are directed to the topic to determine a plurality of required sub-topics;
determine the first content item is missing a sub-topic of the plurality of required sub-topics; and
based at least in part on determining the first content item is missing the required sub-topic, reject the first request to post the first content item;
wherein the transceiver circuitry is further configured to:
receive a second request to post a modified first content item; and
post the modified first content item, based at least in part on determining that the modified first content item includes the missing required sub-topic.
12. The system of claim 11 , wherein the control circuitry is configured to analyze the plurality of second content items by parsing a plurality of online reviews.
13. The system of claim 12 , wherein the first content item is an online review.
14. The system of claim 11 , wherein the machine learning model comprises a neural net.
15. The system of claim 11 , wherein the plurality of required sub-topics are included in a majority of the plurality of second content items.
16. The system of claim 11 , wherein the plurality of required sub-topics are determined using a subset of the plurality of second content items having a rating above a threshold.
17. The system of claim 11 , wherein the control circuitry is further configured to:
analyze the plurality of second content items by identifying keywords in each of the plurality of second content items; and
determine the first content item is missing a sub-topic of the plurality of required sub-topics by determining the first content item is missing a keyword of the identified keywords.
18. The system of claim 11 , wherein:
the first request is to post the first content item to an online review portal; and
the transceiver circuitry makes posts of content items available to a plurality of devices via the online review portal.
19. The system of claim 18 , wherein the plurality of second content items are posts to the online review portal.
20. The system of claim 11 , wherein the control circuitry is further configured to transmit for display a recommendation to modify the first content item to include the missing required sub-topic.