Online forum user depression detection model based on gated convolutional network

A convolutional network, gating technology, applied in biological neural network models, character and pattern recognition, instruments, etc., can solve the problem of unsatisfactory model performance, unable to capture key emotional information, and insufficient functions of depression detection models, etc. question

Inactive Publication Date: 2021-10-29
TIANJIN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, existing depression detection models are not powerful enough to capture key emotional information from the large number of posts published by each user, which makes the performance of these models unsatisfactory.

Method used

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  • Online forum user depression detection model based on gated convolutional network
  • Online forum user depression detection model based on gated convolutional network
  • Online forum user depression detection model based on gated convolutional network

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Embodiment Construction

[0036] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0037] like Figure 1-2 As shown, the online forum user depression detection method based on the gated convolutional network of the present invention uses a model for detecting depression of online paper users based on the gated convolutional network to realize detection. The detection steps of the model are as follows:

[0038] Step 1: Post-level operations

[0039] The input of the model goes through a multi-layer convolutional neural network with gating units, and the convolutional neural network exploits limited contextual information to obtain key features of post representations.

[0040] Post-level operations in MG-CNN, consisting of two convolutional layers and a global aver...

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Abstract

The invention discloses an online forum user depression detection method based on a gated convolutional network, detection is realized by using a model for performing depression detection on an online forum user based on a gated convolutional network, the detection of the model is realized through post-level operation and user-level operation, and post-level characterization is obtained through the post-level operation; through user-level operation, user state representation is obtained, and then probability distribution on a softmax layer output label is utilized to realize detection. The method of the invention can effectively identify languages related to negative emotions in user posts by using gating weights, thereby implementing depression detection.

Description

technical field [0001] The invention relates to the technical field of depression detection, in particular to an online forum user depression detection model based on a gated convolutional network. Background technique [0002] Depression is one of the most common mental health-related disorders and is a leading cause of self-harm and suicide worldwide, affecting millions of people. Early detection and treatment of depression can reduce the damage caused by the disease. But services for the early detection and treatment of depression and other mental illnesses are very limited. And many patients are reluctant to proactively seek help from their healthcare provider. These problems prevent patients from receiving timely treatment, leading to further deterioration of the condition. [0003] More and more people with depression are using online resources (Twitter, websites, Reddit, etc.) to express their psychological problems and seek help. In particular, some online forums...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/20G06K9/62G06N3/04G06N3/08
CPCG16H50/20G06N3/08G06N3/045G06F18/2415
Inventor 饶国政张越丛庆
Owner TIANJIN UNIV
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