US 12,170,670 B2
Use of sentiment analysis to assess trust in a network
Charles Damian O'Neill, Ballymena (GB); Simon James, Newtownards (GB); Kieran Gerald McPeake, Belfast (GB); and Hayden Paul Shorter, Bangor (GB)
Assigned to Juniper Networks, Inc., Sunnyvale, CA (US)
Filed by Juniper Networks, Inc., Sunnyvale, CA (US)
Filed on Dec. 15, 2021, as Appl. No. 17/644,555.
Prior Publication US 2023/0188527 A1, Jun. 15, 2023
Int. Cl. G06F 7/04 (2006.01); G06N 20/00 (2019.01); H04L 9/40 (2022.01); H04L 41/16 (2022.01)
CPC H04L 63/102 (2013.01) [G06N 20/00 (2019.01); H04L 41/16 (2013.01); H04L 63/1408 (2013.01); H04L 63/1425 (2013.01); H04L 63/20 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A method comprising:
performing, by a computing system and based on information collected about a network entity in a computer network, a sentiment analysis associated with the network entity, wherein performing the sentiment analysis includes:
processing the information collected about the network entity in a pipeline that translates raw text into clean text suitable for natural language processing, and
applying a machine learning model to the clean text to predict sentiment associated with the network entity;
determining, by the computing system and based on the sentiment analysis, a trust score for the network entity, wherein determining the trust score includes:
determining a prerequisite sub-score for the network entity based on one or more prerequisites for the network entity,
determining a variable factor sub-score for the network entity based on one or more variable factors for the network entity, and
determining the trust score based on the prerequisite sub-score and the variable factor sub-score; and
performing an action, by the computing system and based on the trust score for the network entity, wherein performing the action includes communicating with a device on the computer network to modify operations within the computer network.