Depression Miner

This project applies data mining techniques to psychology, specifically the field of depression, to detect depressed users in social network services (SNS) or any other data we collect. The expansion of data mining to psychology is of great technical and social significance. It is proved that the pr

Project Title

Depression Miner

Project Area of Specialization

Artificial Intelligence

Project Summary

This project applies data mining techniques to psychology, specifically the field of depression, to detect depressed users in social network services (SNS) or any other data we collect. The expansion of data mining to psychology is of great technical and social significance. It is proved that the proposed model in this proposal could effectively help for detecting depressed ones and preventing suicide among the users.

The technique used in this is sentiment analysis, a NLP(Natural Language Processing) technique that performs on the text to determine whether the author’s intentions towards a particular topic, product, etc. are positive, negative, or neutral. with an algorithm known as SVM ‘Supervised Learning algorithm’. Which uses a kernel trick to transform your data and then based on these transformations it finds an optimal boundary between the possible outputs.

The aim of this system is to diagnose the level of depression of users through the online content they post. The datasets of social network users will be obtained & a predictive machine learning model will be developed and applied for the classification of depressed users using deep learning algorithms.

Our project aims to close the gap by providing authentic report generation and actually provide awareness towards depression. Not only the person will be able to see for itself on what level he is of depression but also be able  to take some suitable steps to overcome it.

Project Objectives

Anxiety and depressive disorders are common in all regions of the world. But unfortunately, Pakistan is one of those vulnerable countries where stress, anxiety and depression are at highest level. Its victims are alarmingly more in urban areas than rural districts. On the socialnetwork, diagnosis of depressed individual using shared content is a challenging task.

Depression is a debilitating mood disorder with a worldwide prevalence estimated at 4.4% . Prevalence estimates in Pakistan range from 22% to 60%, with estimates in Karachi (a populous city of 14.9 million) averaging at 47%. Good quality healthcare in Pakistan is mainly provided by the private sector and requires patients to pay out-of-pocket. This project with a feature of precaution and when to consult a therapist eliminates the problem to some instinct where the report is already generated through this.

The solution to the problem we are now well aware of is provided through our project. Since the full gravity of this situation comes to light with the realization that Pakistan has one of the lowest psychiatrist-to-person ratios in the world. According to the WHO, only 400 psychiatrists and five psychiatric hospitals exist within the entire country for a population exceeding 180 million people. Our project aims to close the gap by providing authentic report generation and actually provide awareness towards depression. Not only the person will be able to see for itself on what level he is of depression but also be able to take some suitable steps to overcome it. Our project will be targeting the medical field where this project can help sustain a digitalized environment.

Most of our society is suffering from bad mental health and the main issue is that they don't even know it.So it is important for them to understand whether they are disturbed or not and whether they need medical help or not.If they are aware of their mental condition than it is easy for others also to understand them and be kind with them rather being harsh on them without knowing in what mental state they are.This is the main challenge which is very hard to address to identify a depressed person and deal with him accordingly we will tackle this issue and try to solve this through our project.

Project Implementation Method

Datasets originating from social networks or from different sites like Kaggle ,Web scraping and Python API’s and libraries and also generate some data by own are valued to many fields such as sociology and psychology. However, the supports from technical perspective are far from enough, and specific approaches are urgently in need. The project applies data mining techniques as the name suggests ‘miner’. Firstly, a sentiment analysis method is proposed utilizing vocabulary and man-made rules to calculate the depression inclination within the users. Secondly, a depression detection model is constructed based on the proposed method where the outcome analyzed as, training of dataset and analyzing the condition of the user, if the person is depressed then on what level which can vary between mild to extreme based on the keywords. Third feature includes the consultant to a doctor or remedies/precautions to be taken with another add on will be the authentication of the result where doctor can compare and use the generated report.

Our app will login the user through social app and through web scraping we will get recent data of the user. The proposed project will solve the problem first is the pertaining of dataset training it and analyzing the mental condition of the user on our trained model.Secondly, the project will determine at which level of depression the user is currently.Third, if he is in initial to mild condition what precaution he should take and if it is on high or extreme scale listing the precautions along with the consultant of the therapist recommendation.Lastly, will be the authentic report generation which can help the consultant analyze and better understand the problem of the user.

Benefits of the Project

• This project can be used in hospitals by doctors and therapist to correlate data making it efficient and effective by minimizing the diagnose part.

• Therapist or psychiatrist can authenticate and use it as an actual report.

• The project can be used in collages, universities and companies for mental health inspection.

• Overall, provides benefits to individuals to track and   monitor their own mental health by taking necessary precautions.

• Targeting medical field to make process digitalized.

Technical Details of Final Deliverable

There will be a machine learning model trained on historical data. It will be converted into an API or web service and integrated into our mobile app.

User will login in our app through/via his social site and we will try to get his current data of social platform through web scraping, Now his current data will be checked on our trained model and results will be generated in form of an authentic report.

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

Medical , Health

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com