Mental illness is quickly becoming one of the most prevalent public health problems worldwide. Social network platforms, where users can express their emotions, feelings, and thoughts, are a valuable source of data for researching mental health, and techniques based on machine learning are increasingly used for this purpose.

Despite an increasing number of studies investigating mental health issues using social network data, some common problems persist. Assembling large, high-quality datasets of social media users with mental disorder is problematic, not only due to biases associated with the collection methods, but also with regard to managing consent and selecting appropriate analytics techniques.

study examined 467 young adults for their time spent using social media, importance of social media in their lives and tendency to engage in vaguebooking (posting unclear but alarming sounding posts to get attention). Outcomes considered included general mental health symptoms, suicidal ideation, loneliness, social anxiety and decreased empathy. Results indicated that social media use was not predictive of impaired mental health functioning. However, vaguebooking was predictive of suicidal ideation, suggesting this particular behavior could be a warning sign for serious issues.

Social media use predicted low mood, but did not predict self‐esteem and paranoia. Posting about feelings and venting on social media predicted low mood and self‐esteem and high paranoia, whilst posting about daily activities predicted increases in positive affect and self‐esteem and viewing social media newsfeeds predicted reductions in negative affect and paranoia. Perceptions of low social rank when using social media predicted low mood and self‐esteem and high paranoia. The impact of social media use did not differ between participants with and without psychosis; although, experiencing psychosis moderated the relationship between venting and negative affect. Social media use frequency was lower in people with psychosis.

New research led by Sarah Coyne, a professor of family life at Brigham Young University, found that the amount of time spent on social media is not directly increasing anxiety or depression in teenagers, instead mental health is a multi-process syndrome where no one stressor is likely the cause of depression or anxiety.

There are several reasons where the use of social media has effects on mental health, including:
 reducing the time allocated to sleep and rest, and the deterioration of the quality of this time,
 the lack from direct social and human communication, and away from physical activities and sports,
 in addition, exposure to bullying on the social media, which is just as harmful as other bullying, that's because it's hard to get away from, and it can reach people anytime and anywhere.
Together, these causes, especially the cyberbullying, have a negative impact on mental health.

Despite an increasing number of studies investigating mental health issues using social network data, some common problems persist. Assembling large, high-quality datasets of social media users with mental disorder is problematic, not only due to biases associated with the collection methods, but also with regard to managing consent and selecting appropriate analytics techniques.


In conclusion, it is clear that during the past 10 years, online social networking has caused significant changes in the way people communicate and interact. It is unclear, however, whether some of these changes affect normal aspects of human behavior and cause psychiatric disorders. In the future, additional research will be needed to identify and describe the potential relationship between the use of SNS and various mental health issues.