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

Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

490
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
490
Long-term Depression01:05

Long-term Depression

33.3K
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.
33.3K
Social Proof00:52

Social Proof

32.4K
Social proof is a form of persuasion based on comparison and conformity. People compare their behavior and actions to what others are doing and will change to conform to do what their peers do.
32.4K
The Sense of Self: Reflected Self-Appraisal and Social Comparison02:57

The Sense of Self: Reflected Self-Appraisal and Social Comparison

56.1K
According to Charles Cooley, we base our image on what we think other people see (Cooley 1902). We imagine how we must appear to others, then react to this speculation. We don certain clothes, prepare our hair in a particular manner, wear makeup, use cologne, and the like—all with the notion that our presentation of ourselves is going to affect how others perceive us. We expect a certain reaction, and, if lucky, we get the one we desire and feel good about it. But more than that, Cooley...
56.1K
Social Scripts02:10

Social Scripts

10.3K
People tend to know what behavior is expected of them in specific, familiar settings. A script is a person’s knowledge about the sequence of events expected in a specific setting (Schank & Abelson, 1977). Essentially, scripts are a particular kind of schema, one containing default values for the features within an event. In the restaurant example, the script's features include the props (e.g., tables, menu, food, and money), the roles to be played (e.g., customer and waiter),...
10.3K
Social Traps01:41

Social Traps

26.9K
Social traps are negative situations where people get caught in a direction or relationship that later proves to be unpleasant, with no easy way to back out of or avoid. The concept was orignally introduced by John Platt who applied psychology to Garrett Hardin's "Tragedy of the Commons", where in New England herd owners could let their cattle graze in the common ground. This situation seems like a good idea, but an individual could have an advantage. If they owned...
26.9K

You might also read

Related Articles

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

Sort by
Same author

Improvement of Health-related Quality of Life among the Children by School Nurse Program: A Nonrandomized Controlled Trial.

Indian journal of public health·2026
Same author

An integrated deep learning framework leveraging NASNet and vision transformer with MixProcessing for accurate and precise diagnosis of lung diseases.

SLAS technology·2026
Same author

Impact of mobile health-based nutritional education on hemoglobin levels in anemic adolescent girls in rural Bangladesh: a randomized controlled trial.

BMC public health·2025
Same author

An integrated deep learning framework using adaptive enhanced vision fusion and modified mobilenet architecture for precision classification of skin diseases with enhanced diagnostic performance.

SLAS technology·2025
Same author

Health educational intervention by school nurses to prevent children's helminthic infection in Bangladesh: A cluster non-randomized controlled trial.

Journal of education and health promotion·2025
Same author

Prevalence and influencing factors with knowledge, attitude, and practice toward anemia among school-going adolescent girls in rural Bangladesh.

PloS one·2024

Related Experiment Video

Updated: Feb 5, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.5K

Depression detection from social network data using machine learning techniques.

Md Rafiqul Islam1, Muhammad Ashad Kabir2, Ashir Ahmed3

  • 11Department of Computer Science & Engineering, Islamic University of Technology (IUT), Dhaka, Bangladesh.

Health Information Science and Systems
|September 7, 2018
PubMed
Summary
This summary is machine-generated.

This study uses machine learning on Facebook data to detect depression. Decision Tree models showed the highest accuracy in identifying mental health issues from user sentiments.

Keywords:
DepressionEmotionsSentiment analysisSocial network

More Related Videos

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

1.0K
Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems
08:42

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems

Published on: May 5, 2015

12.6K

Related Experiment Videos

Last Updated: Feb 5, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.5K
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

1.0K
Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems
08:42

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems

Published on: May 5, 2015

12.6K

Area of Science:

  • Computational Social Science
  • Psychiatry
  • Machine Learning

Background:

  • Social networks facilitate user communication and sentiment sharing.
  • Analyzing social media data offers insights into user moods and attitudes.
  • Detecting depression via social networks is an emerging field with unexplored dimensions.

Purpose of the Study:

  • To perform depression analysis using publicly available Facebook data.
  • To investigate the effectiveness of machine learning for depression detection.
  • To identify scalable and efficient methods for analyzing user sentiments related to mental health.

Main Methods:

  • Utilized a machine learning technique for depression analysis.
  • Collected Facebook data from an online public source.
  • Evaluated the method's efficiency using psycholinguistic features.

Main Results:

  • The proposed machine learning method significantly improved accuracy and reduced classification error rates.
  • Decision Tree (DT) demonstrated the highest accuracy among tested machine learning approaches for depression detection.
  • Psycholinguistic features were effective in evaluating the proposed method's performance.

Conclusions:

  • Machine learning techniques offer effective solutions for identifying mental health challenges in Facebook users.
  • This research highlights the potential of computational methods in mental healthcare.
  • The findings support the use of social network data analysis for understanding user well-being.