Stress Detection Based on Social Media Blogs

Project Code :TCMAPY465

Objective

The main objective of this project is to create a Effective Detection system for stress detection among individuals and taking necessary precautions to prevent the users from committing suicide.

Abstract

The technological advancement and significant rise in the usage of social media has resulted in major psychological health problems such as stress, anxiety etc. These challenges can be analyzed and prevention strategies can be formulated. To overcome these severe problems, the urgent need is to monitor the blogs in social media as it is irrepressible by humans due to their strong desire towards SMEs (Social Media Environments). Traditional methods such as questionnaires and interviews were conducted by psychologists but these processes are time-consuming and hysteric. 

In this paper we have surveyed various stress detection strategies and found to be ineffective to detect stress from social media. In this paper we proposed an Effective Stress Detection method to utilize the ontology for stress detection among individuals and taking necessary precautions to prevent the users from committing suicide. Ontology is the keyword matching search process used in social media to identify the stress-related messages shared among individuals with improved accuracy.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

HARDWARE SPECIFICATIONS:

  • Processor: I3/Intel
  • Processor RAM: 4GB (min)
  • Hard Disk: 128 GB
  • Key Board: Standard Windows Keyboard
  • Mouse: Two or Three Button Mouse
  • Monitor: Any

SOFTWARE SPECIFICATIONS:

  • Operating System: Windows 7+
  • Server-side Script: Python 3.6+
  • IDE: Pycharm IDE
  • Libraries Used: Pandas, Numpy, Sklearn, Catboost

Learning Outcomes

  • Scope of Real Time Application Scenarios
  • What type of technology versions are used
  • Working Procedure
  • Introduction to basic technologies used for
  • How project works.
  • Input and Output modules
  • Frame work use
  • Datasets properties
  • Deep learning algorithms.
  • Data pre-processing techniques
  • What is ANN model
  • Project Development Skills:
    • Problem analyzing skills.
    • Problem solving skills.
    • Creativity and imaginary skills.
    • Programming skills.
    • Deployment.
    • Testing skills.
    • Debugging skills.
    • Project presentation skills.
    • Thesis writing skills.

Demo Video

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