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相关论文: See and Read: Detecting Depression Symptoms in Hig…

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Depression is a common mental illness that has to be detected and treated at an early stage to avoid serious consequences. There are many methods and modalities for detecting depression that involves physical examination of the individual.…

人工智能 · 计算机科学 2022-02-08 Kayalvizhi S , Thenmozhi D

Social media channels, such as Facebook, Twitter, and Instagram, have altered our world forever. People are now increasingly connected than ever and reveal a sort of digital persona. Although social media certainly has several remarkable…

社会与信息网络 · 计算机科学 2020-08-26 Hatoon S. AlSagri , Mourad Ykhlef

Depression is debilitating, and not uncommon. Indeed, studies of excessive social media users show correlations with depression, ADHD, and other mental health concerns. Given that there is a large number of people with excessive social…

计算与语言 · 计算机科学 2023-10-04 Dean Ninalga

Depression is a common disease worldwide. It is difficult to diagnose and continues to be underdiagnosed. Because depressed patients constantly share their symptoms, major life events, and treatments on social media, researchers are turning…

计算与语言 · 计算机科学 2025-10-27 Wenli Zhang , Jiaheng Xie , Zhu Zhang , Xiang Liu

With ubiquity of social media platforms, millions of people are sharing their online persona by expressing their thoughts, moods, emotions, feelings, and even their daily struggles with mental health issues voluntarily and publicly on…

Social network plays an important role in propagating people's viewpoints, emotions, thoughts, and fears. Notably, following lockdown periods during the COVID-19 pandemic, the issue of depression has garnered increasing attention, with a…

计算与语言 · 计算机科学 2023-06-28 Yan Shi , Yao Tian , Chengwei Tong , Chunyan Zhu , Qianqian Li , Mengzhu Zhang , Wei Zhao , Yong Liao , Pengyuan Zhou

Depression is the most common mental health disorder, and its prevalence increased during the COVID-19 pandemic. As one of the most extensively researched psychological conditions, recent research has increasingly focused on leveraging…

Depressive disorders constitute a severe public health issue worldwide. However, public health systems have limited capacity for case detection and diagnosis. In this regard, the widespread use of social media has opened up a way to access…

计算与语言 · 计算机科学 2023-10-10 Anxo Pérez , Neha Warikoo , Kexin Wang , Javier Parapar , Iryna Gurevych

Depression is one of the most common mental disorders affecting an individual's personal and professional life. In this work, we investigated the possibility of utilizing social media posts to identify depression in individuals. To achieve…

计算与语言 · 计算机科学 2024-05-14 Nandigramam Sai Harshit , Nilesh Kumar Sahu , Haroon R. Lone

Depression is a significant issue nowadays. As per the World Health Organization (WHO), in 2023, over 280 million individuals are grappling with depression. This is a huge number; if not taken seriously, these numbers will increase rapidly.…

计算与语言 · 计算机科学 2024-04-23 Muhammad Osama Nusrat , Waseem Shahzad , Saad Ahmed Jamal

The most common mental disorders experienced by a person in daily life are depression and anxiety. Social stigma makes people with depression and anxiety neglected by their surroundings. Therefore, they turn to social media like Twitter for…

计算与语言 · 计算机科学 2023-01-12 Kuncahyo Setyo Nugroho , Ismail Akbar , Affi Nizar Suksmawati , Istiadi

With more than 300 million people depressed worldwide, depression is a global problem. Due to access barriers such as social stigma, cost, and treatment availability, 60% of mentally-ill adults do not receive any mental health services.…

计算机视觉与模式识别 · 计算机科学 2018-11-28 Albert Haque , Michelle Guo , Adam S Miner , Li Fei-Fei

Depression is a mental health disorder that has a profound impact on people's lives. Recent research suggests that signs of depression can be detected in the way individuals communicate, both through spoken words and written texts. In…

计算与语言 · 计算机科学 2023-10-18 Fardin Ahsan Sakib , Ahnaf Atef Choudhury , Ozlem Uzuner

Depression is the leading cause of disability worldwide. Initial efforts to detect depression signals from social media posts have shown promising results. Given the high internal validity, results from such analyses are potentially…

社会与信息网络 · 计算机科学 2020-06-16 Lucia Lushi Chen , Walid Magdy , Heather Whalley , Maria Wolters

Using Instagram data from 166 individuals, we applied machine learning tools to successfully identify markers of depression. Statistical features were computationally extracted from 43,950 participant Instagram photos, using color analysis,…

社会与信息网络 · 计算机科学 2016-08-16 Andrew G. Reece , Christopher M. Danforth

We describe the development of a model to detect user-level clinical depression based on a user's temporal social media posts. Our model uses a Depression Symptoms Detection (DSD) classifier, which is trained on the largest existing samples…

计算与语言 · 计算机科学 2023-03-31 Nawshad Farruque , Randy Goebel , Sudhakar Sivapalan , Osmar R. Zaïane

Depression and anxiety are psychiatric disorders that are observed in many areas of everyday life. For example, these disorders manifest themselves somewhat frequently in texts written by nondiagnosed users in social media. However,…

计算与语言 · 计算机科学 2020-11-11 David Owen , Jose Camacho Collados , Luis Espinosa-Anke

Mental disorders such as depression and suicidal ideation are hazardous, affecting more than 300 million people over the world. However, on social media, mental disorder symptoms can be observed, and automated approaches are increasingly…

信息检索 · 计算机科学 2023-01-26 Ramin Safa , S. A. Edalatpanah , Ali Sorourkhah

Social media has recently emerged as a premier method to disseminate information online. Through these online networks, tens of millions of individuals communicate their thoughts, personal experiences, and social ideals. We therefore…

社会与信息网络 · 计算机科学 2016-07-26 Moin Nadeem

With the rise of social media, millions of people are routinely expressing their moods, feelings, and daily struggles with mental health issues on social media platforms like Twitter. Unlike traditional observational cohort studies…

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