Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Call For Paper : Vol. 9, Issue 5 , 2022
A Proposed System on Detecting Stress Based On Social Interactions on Social Networks

Author : Indu Dokare 1 Gayatri Pawar 2 Manisha Mirchandani 3 Shreya Narsapur 4 Kajal Rajani 5

Date of Publication :14th March 2018

Abstract: Stress is essentially humans' response to various types of desires or threats. This response, when working properly, can help us to stay focussed, energized and intellectually active; but if it is out of proportion, it can certainly be harmful leading to depression, anxiety, hypertension and a host of threatening disorders. Cyberspace is a huge soap box for people to post anything and everything that they experience in their day-to-day lives. Subsequently, it can be used as a very effective tool in determining the stress levels of an individual based on the posts and status updates shared by him/her. This is a proposal for a website which takes the Twitter username of the subject as an input, scans and analyses the subject's profile by performing Sentiment Analysis and gives out results. These results suggest the overall stress levels of the subject and give an overview of his/her mental and emotional state. The tool used for analysis of the social media account is Rapidminer. Rapidminer is an environment for various data mining and machine learning procedures with a very effective and simple GUI.[1]

Reference :

    1.  Y. Ramamohan, K. Vasantharao, C. Kalyana Chakravarti, A.S.K.Ratnam, “A Study of Data Mining Tools in Knowledge Discovery Process,” International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume2, Issue-3, July 2012.
    2. Apoorv Agarwal, Boyi Xie, Ilia Vovsha, Owen Rambow, Rebecca Passonneau, “Sentiment Analysis of Twitter Data,” unpublished.
    3.  “Sentiment Analysis of Twitter Data,” Available: https://www.slideshare.net/sumit786raj/sentimen t-analysis-of-twitter-data
    4.  “Integrating RapidMiner into your application,” Available: https://community.rapidminer.com/t5/OriginalRapid-I-Forum/Integrating-RapidMiner-intoyour-application/td-p/7071

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