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A Survey on Mental Health Prediction Using Social Media Network

EasyChair Preprint no. 3521

3 pagesDate: May 30, 2020


Social media network is an network that gets utilized a great deal and allows people to connect with others, sharing and accepting data with them, all while utilizing the web to convey. Adults and especially young generation the same utilize social media network on an everyday and once in a while hourly premise. They check social media network commonly every day to see the most recent news, photographs, sharing knowledge, thoughts or opinions within a community of friends. Social media network utilization on a daily basis is influencing emotional wellness in a negative manner that leads towards the mental illness like depression and other mental diseases. The main purpose of this study is to extract and examine the previous work on mental illness via social media network. The basic aim of this paper is survey from the previous work done in detection of mental illness due excess use of social media network to current research work for detection of mental illness via social media network. The significant discoveries from the previous related work of literature for detection of mental illness many of the researchers used different supervised machine learning techniques depends upon the features that will extract from the data which is collected through social media logs of the group of users or individual. The online social networking applications such as Twitter, Facebook, Instagram is a major data sources of online social media with English is the common language that individual or group of users express their emotion, feeling, and also share their views used for mental health detection. In addition, the number researcher found a few challenges like language obstruction, user account privacy, and limited features selection from the big data source of social media network.

Keyphrases: Big Data, Depression, Social Media Network, Supervised Machine Learning

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Sushant A. Patinge and Vijaya K. Shandilya},
  title = {A Survey on Mental Health Prediction Using Social Media Network},
  howpublished = {EasyChair Preprint no. 3521},

  year = {EasyChair, 2020}}
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