UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 5 Issue 9
September-2018
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRE006036


Registration ID:
187660

Page Number

215-220

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Title

Minimizing and Detecting Stress in Social Networks based on Social Interactions

Authors

Abstract

Psychological stress is threatening people’s health. It is non-trivial to detect stress timely for proactive care. With the popularity of social media, people are used to sharing their daily activities and interacting with friends on social media platforms, making it feasible to leverage online social network data for stress detection. In this paper, we find that users stress state is closely related to that of his/her friends in social media, and we employ a large-scale dataset from real-world social platforms to systematically study the correlation of users’ stress states and social interactions. We first define a set of stress-related textual, visual, and social attributes from various aspects, and then propose a novel hybrid model - a Factor Graph Model (FGM) combined with Convolutional Neural Network (CNN) to leverage tweet content and social interaction information for stress detection. Experimental results show that the proposed model can improve the detection performance by 6-9 percent in F1-score. By further analyzing the social interaction data, we also discover several intriguing phenomena, i.e., the number of social structures of sparse connections (i.e., with no delta connections) of stressed users is around 14 percent higher than that of non-stressed users, indicating that the social structure of stressed users’ friends tend to be less connected and less complicated than that of non-stressed users.

Key Words

Stress detection, factor graph model, micro-blog, social media, healthcare, social interaction

Cite This Article

"Minimizing and Detecting Stress in Social Networks based on Social Interactions", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 9, page no.215-220, September-2018, Available :http://www.jetir.org/papers/JETIRE006036.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Minimizing and Detecting Stress in Social Networks based on Social Interactions", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 9, page no. pp215-220, September-2018, Available at : http://www.jetir.org/papers/JETIRE006036.pdf

Publication Details

Published Paper ID: JETIRE006036
Registration ID: 187660
Published In: Volume 5 | Issue 9 | Year September-2018
DOI (Digital Object Identifier):
Page No: 215-220
Country: Chennai, Tamil Nadu, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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