Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Long-term Depression01:05

Long-term Depression

31.3K
Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
31.3K
Depressive Disorders: Etiology01:27

Depressive Disorders: Etiology

153
Depressive disorders result from a complex interplay of biological, psychological, and sociocultural factors, each contributing uniquely to the development and persistence of the condition. Understanding these factors provides critical insight into the multifaceted nature of depression.
Biological Factors in Depression
Biological predispositions significantly influence the risk of developing depressive disorders. Genetic studies highlight the role of variations in the serotonin transporter...
153
Weighted Mean00:57

Weighted Mean

5.3K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
5.3K
Depressive Disorders: MDD and Dysthymia01:27

Depressive Disorders: MDD and Dysthymia

201
Depressive disorders are a group of mental health conditions characterized by pervasive feelings of sadness, diminished pleasure in life, and a significant impact on daily functioning. These conditions are most prevalent in individuals during their 30s and affect women at twice the rate of men. Contrary to popular belief, younger individuals are generally more susceptible to these disorders than older adults. Two key types of depressive disorders include Major Depressive Disorder (MDD) and...
201
Self-Presentation: Self-Monitoring and Self-Handicapping02:05

Self-Presentation: Self-Monitoring and Self-Handicapping

39.6K
People can go to great lengths to protect their self-image and present themselves in ways that they want others to see them. Sociologist Erving Goffman presented the idea that a person is like an actor on a stage. Calling his theory dramaturgy, Goffman believed that we use “impression management” to present ourselves to others as we hope to be perceived. Each situation is a new scene, and individuals perform different roles depending on who is present (Goffman, 1959). Think about...
39.6K
Depression: Overview01:18

Depression: Overview

322
Depression is a prevalent mental illness marked by persistent sadness and lack of interest in previously enjoyable activities. It can take several forms, including major depression, persistent depressive disorder, and bipolar I and II disorders. Symptoms range from emotional changes like chronic worry to physical changes like sleep disturbances and suicidal thoughts. From a neurobiological perspective, depression is believed to be triggered by abnormalities in the brain's prefrontal cortex,...
322

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Exploiting topic analysis models to explore psychological dimensions in social media data.

Scientific reports·2026
Same author

Explainable depression symptom detection in social media.

Health information science and systems·2024
See all related articles

Related Experiment Video

Updated: Aug 26, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

673

Automatic depression score estimation with word embedding models.

Anxo Pérez1, Javier Parapar1, Álvaro Barreiro1

  • 1Information Retrieval Lab, CITIC, Universidade da Coruña, Campus de Elviña s/n, 15071 A Coruña, Spain.

Artificial Intelligence in Medicine
|October 7, 2022
PubMed
Summary

This study introduces a new method using neural language models to automatically estimate depression severity from social media posts. This approach offers a feasible alternative for early detection, even with limited data.

Keywords:
Depression predictionNeural language modelsSocial mediaWord embeddings

More Related Videos

Animal Models of Depression - Chronic Despair Model CDM
05:47

Animal Models of Depression - Chronic Despair Model CDM

Published on: September 23, 2021

7.4K
Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
05:19

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment

Published on: July 7, 2023

2.4K

Related Experiment Videos

Last Updated: Aug 26, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

673
Animal Models of Depression - Chronic Despair Model CDM
05:47

Animal Models of Depression - Chronic Despair Model CDM

Published on: September 23, 2021

7.4K
Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
05:19

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment

Published on: July 7, 2023

2.4K

Area of Science:

  • Computational linguistics
  • Mental health informatics
  • Artificial intelligence in healthcare

Background:

  • Depression is a prevalent mental health disorder, yet early and efficient detection remains challenging.
  • Traditional diagnostic methods rely on self-report questionnaires, which can be influenced by social stigma.
  • Automated approaches are needed to overcome limitations of current diagnostic tools.

Purpose of the Study:

  • To develop and evaluate novel methods for automatically estimating depression severity using social media data.
  • To explore the effectiveness of neural language models in capturing depression symptoms from user writings.
  • To address the eRisk 2020 task of Measuring the Severity of the Signs of Depression.

Main Methods:

  • Two distinct neural language model-based methods were developed: one analyzing general user language and another focusing on posts mentioning specific depression symptoms.
  • Both methods aimed to automatically estimate the Beck Depression Inventory (BDI-II) total score.
  • Benchmark Reddit data was utilized for evaluating the proposed methods.

Main Results:

  • Neural language models proved to be a feasible alternative for estimating depression severity.
  • The proposed methods demonstrated effectiveness even with limited training data.
  • The study successfully addressed the challenge of automatic depression severity estimation from social media.

Conclusions:

  • Automated estimation of depression severity from social media using neural language models is a viable approach.
  • This technology can potentially aid in the early detection of depression, complementing traditional methods.
  • Further research can refine these models for broader clinical application.