Open Access and Peer-reviewed
Home Journal Issues Guide for Authors Editorial Board Aims & Scope About Journal News & Announcements


Research Article 


DETECTING SOCIAL NETWORK USERS STRESS BASED ON ATTRIBUTES CATEGORIZATION

AMARAM RAMYA, Dr. M.NAGA LAKSHMI.

Abstract
Psychological stress and anxiety is turning into a risk to humans's fitness currently days. With the short charge of existence, an increasing number of people are really feeling confused. It is not smooth to pick out people tension in an early time to shield individual. With the recognition of on-line social networking, human beings are used to sharing their ordinary obligations and additionally interacting with friends using net-based networking media levels, making it feasible to make use of online social network information for strain detection. In our machine we find that customers stress and anxiety usa can be very intently pertaining to that of his/her close buddies in social networks, and utilize a huge scale dataset from real-world social structures to systematically look at the relationship of individuals' anxiety states and also social interactions In our device, we find out that individuals tension us of a is cautiously associated with that of his/her near friends in social media net web sites, in addition to we use a large dataset from actual-global social systems to systematically research the relationship of people' strain states and social interactions. We first of all specify a group of pressure-associated textual, seen, and social features from numerous components, and afterwards proposed a plot.Experimental effects display that the proposed layout can enhance the detection performance.With the help of listing we build a website for the customers to become privy to their tension charge diploma and also can check other associated sports. By extra analyzing the social interplay facts, we furthermore discover a number of interesting phenomena, i.E. The extensive kind of social structures of sporadic hyperlinks (i.E. With no delta connections) of confused out human beings is round 14% higher than that of nonstressed customers, displaying that the social shape of harassed clients' pals will be predisposed to be plenty much less linked and masses plenty less complicated than that of non-compelled individuals.

Key words: CNN, Large scale, social media platform


 
ARTICLE TOOLS
Abstract
PDF Fulltext
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by AMARAM RAMYA
Articles by Dr. M.NAGA LAKSHMI
on Google
on Google Scholar


How to Cite this Article
Pubmed Style

AMARAM RAMYA, Dr. M.NAGA LAKSHMI. DETECTING SOCIAL NETWORK USERS STRESS BASED ON ATTRIBUTES CATEGORIZATION. EEO. 2021; 20(5): 4336-4341. doi:10.17051/ilkonline.2021.05.476


Web Style

AMARAM RAMYA, Dr. M.NAGA LAKSHMI. DETECTING SOCIAL NETWORK USERS STRESS BASED ON ATTRIBUTES CATEGORIZATION. http://ilkogretim-online.org//?mno=69482 [Access: April 09, 2021]. doi:10.17051/ilkonline.2021.05.476


AMA (American Medical Association) Style

AMARAM RAMYA, Dr. M.NAGA LAKSHMI. DETECTING SOCIAL NETWORK USERS STRESS BASED ON ATTRIBUTES CATEGORIZATION. EEO. 2021; 20(5): 4336-4341. doi:10.17051/ilkonline.2021.05.476



Vancouver/ICMJE Style

AMARAM RAMYA, Dr. M.NAGA LAKSHMI. DETECTING SOCIAL NETWORK USERS STRESS BASED ON ATTRIBUTES CATEGORIZATION. EEO. (2021), [cited April 09, 2021]; 20(5): 4336-4341. doi:10.17051/ilkonline.2021.05.476



Harvard Style

AMARAM RAMYA, Dr. M.NAGA LAKSHMI (2021) DETECTING SOCIAL NETWORK USERS STRESS BASED ON ATTRIBUTES CATEGORIZATION. EEO, 20 (5), 4336-4341. doi:10.17051/ilkonline.2021.05.476



Turabian Style

AMARAM RAMYA, Dr. M.NAGA LAKSHMI. 2021. DETECTING SOCIAL NETWORK USERS STRESS BASED ON ATTRIBUTES CATEGORIZATION. Elementary Education Online, 20 (5), 4336-4341. doi:10.17051/ilkonline.2021.05.476



Chicago Style

AMARAM RAMYA, Dr. M.NAGA LAKSHMI. "DETECTING SOCIAL NETWORK USERS STRESS BASED ON ATTRIBUTES CATEGORIZATION." Elementary Education Online 20 (2021), 4336-4341. doi:10.17051/ilkonline.2021.05.476



MLA (The Modern Language Association) Style

AMARAM RAMYA, Dr. M.NAGA LAKSHMI. "DETECTING SOCIAL NETWORK USERS STRESS BASED ON ATTRIBUTES CATEGORIZATION." Elementary Education Online 20.5 (2021), 4336-4341. Print. doi:10.17051/ilkonline.2021.05.476



APA (American Psychological Association) Style

AMARAM RAMYA, Dr. M.NAGA LAKSHMI (2021) DETECTING SOCIAL NETWORK USERS STRESS BASED ON ATTRIBUTES CATEGORIZATION. Elementary Education Online, 20 (5), 4336-4341. doi:10.17051/ilkonline.2021.05.476








AUTHOR LOGIN

REVIEWER LOGIN

Indexed
&
Abstracted


Indexing

İlköğretim Online (IOO) - Elementary Education Online (EEO) is indexed in:


ABOUT JOURNAL
POLICIES
STATEMENTS