scholarly journals Methods to Perform Opinion Mining and Sentiment Analysis to Detect Factors Affecting Mental Health

2021 ◽  
Vol 11 (1) ◽  
pp. 70-72
Author(s):  
Ravindra Kumar ◽  
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Sentiment Analysis ◽  
Opinion Mining ◽  
Background Knowledge ◽  
Factors Affecting ◽  
Opinion Extraction ◽  
Main Target

Sentimental analysis and opinion extraction are emerging fields at AI. These approaches help organizations to use the opinions, sentiments, and subjectivity of their consumers in decision-making. Sentiments, views, and opinions show the feeling of the consumers towards a given product or service. In recent years, Opinion Mining and Sentiment Analysis has become an important tool to detect the factors affecting mental health. It’s Also true that human biasness is available in giving opinions, but it can be eliminated through the use of algorithms to get better results. However, it is crucial to remember that the developers are human and might pass the biasness to the algorithms during training. The main target of this paper is to give background knowledge on opinion extraction and sentimental analysis and how factors affecting mental health can be collected. The paper aimed to use interested individuals in knowing some of the algorithms in opinions extraction and sentimental analysis. The paper also provides benefits of using sentiment analysis and some of the challenges of using the algorithms.

scholarly journals Addressing funding issues for Danish mental health NGOs

2018 ◽  
Vol 17 (2) ◽  
pp. 79-89
Author(s):  
Nawal Farhat Aguilar ◽  
Zaza Nadja Lee Hansen
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Literature Review ◽  
Key Factors ◽  
Content Type ◽  
Factors Affecting ◽  
Non Governmental Organizations ◽  
Decision Making Framework ◽  
Optimal Approach

Purpose Research has shown that non-governmental organizations (NGOs) often fail to appreciate that in their market, donors represent clients. Moreover, the unstable income characteristics of NGOs emphasize the importance of conducting market analysis specific to such organizations. The purpose of this paper is to identify key factors that influence fundraising success for mental health NGOs and determine the most advantageous fundraising approach based on a mixed-methods study that encompass a literature review, two surveys and a case study. Design/methodology/approach Based on a structured literature review, the most important factors affecting NGO fundraising are unified into a decision-making framework. This framework is tested using a triangulation approach by combining quantitative and qualitative methods. The former based on a general survey and the latter based on a case study. Findings The results highlight 15 key factors determining the optimal approach for mental health NGOs when fundraising in Denmark. Practical implications The decision-making framework can be used to assess the most advantageous fundraising approach based on a variety of internal and external circumstances. Originality/value While private firms develop exhaustive market analyses, NGOs often lack analyses to cope with fluctuating environments and changing customer needs. This paper addresses this gap by identifying key factors that determine an optimal fundraising approach and proposes a novel decision-making framework for practitioners.

scholarly journals Impact of Difficulties Faced by Adolescents in Making Career Decision on their Mental Health

2019 ◽  
Vol 9 (2) ◽  
pp. 1-8
Author(s):  
Ayesha Khan ◽  
Adeela Rehman
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Peer Pressure ◽  
Career Decision ◽  
Psychological Effect ◽  
Career Decision Making ◽  
Factors Affecting ◽  
A Value ◽  
Significant Difference ◽  
The Impact

This research aimed to explore the impact of difficulties faced by adolescents in making a career decision on their mental health. The objective of the research was to explore the factors affecting career decision making and to explore the psychological effect of career decision making difficulties. A quantitative research design was used to collect data through online survey by random sampling method in which a sample of 70 adolescents aged between 18-24 both male (28) and female (42) were collected from Rawalpindi, Pakistan and then analyzed on SPSS. A correlation (p: .002) was found between career indecisiveness and mental health. Independent T test result suggested that gender difference exists with respect to career indecisiveness indicating a value of p to be .01, while one way ANOVA indicated a value of p to be .382, showing that no significant difference exist with respect to respondents age. A chi square result indicated the factors affecting career decision making to be parental (p: .000) and peer pressure (p: .002) and indicated that career decision making time period is stressful for adolescents who feel difficulty in making a career decision (p: .000) indicating a psychological effect. Thus, the hypothesis was proved that adolescents face career decision making difficulties which negatively impact their mental health and it is recommended that they should be given career guidance to help them out in exploring what they really want to do in their lives instead of making a wrong career and regretting it later.

scholarly journals Sentiment Trend Analysis of Big Data

2019 ◽  
Vol 8 (10) ◽  
pp. 59-64
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Big Data ◽  
Sentiment Analysis ◽  
Real Time ◽  
Language Processing ◽  
Opinion Mining ◽  
Data Sources ◽  
Product Reviews

Various fields like Text Mining, Linguistics, Decision Making and Natural Language Processing together form the basis for Opinion Mining or Sentiment Analysis. People share their feelings, observations and thoughts on social media, which has emerged as a powerful tool for rapidly growing enormous repository of real time discussions and thoughts shared by people. In this paper, we aim to decipher the current popular opinions or emotions from various sources, hence, contributing to sentiment analysis domain. Text from social media, blogs and product reviews are classified according to the sentiment they project. We re-examine the traditional processes of sentiment extraction, to incorporate the increase in complexity and number of the data sources and relevant topics, while re-populating the meaning of sentiment. Working across and within numerous streams of social media, expression of sentiment and classification of polarity is re-examined, thereby redefining and enhancing the realm of sentiment. Numerous social media streams are analyzed to build datasets that are topical for each stream and are later polarized according to their sentiment expression. In conclusion, defining a sentiment and developing tools for its analysis in real time of human idea exchange is the motive.

scholarly journals Word Embedding and Feature Reduction for Sentiment Analysis Using GA

2020 ◽  
pp. 111-117
Author(s):  
Prajakta P. Shelke ◽  
Ankita N. Korde
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Sentiment Analysis ◽  
Recommendation System ◽  
Opinion Mining ◽  
Hybrid Approach ◽  
Feature Reduction ◽  
Word Embedding ◽  
Support Vector ◽  
Svm Classifier

Sentiment analysis (SA), also called as opinion mining is the technique for the removal of opinions of a specific entity or feature from reviews dataset. The opinions of other users help in decision making process of people. This paper studies different methods that are aimed at SA. These approaches vary from semantic based methods, machine learning, neural networks, syntactical methods with each having its own strength. Although hybrid approach also exists where the idea is to combine strengths of two or more methods to increase the accuracy. A framework in which sentiment analysis is done by using word embedding and feature reduction techniques is also proposed. Word embedding is a technique in which low-dimensional vector representation of words is provided. Feature reduction method is used with Support Vector Machine (SVM) classifier. The framework will perform sentiment analysis of user opinions by using a machine learning approach and provides a recommendation system for the ease of decision making for users. The proposed system in this paper has solved the scalability problem and improved the accuracy.

Post COVID-19 Potentials and Innovation: The Future Supply Chain

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 1054-1057
Author(s):  
Bindu Swetha Pasuluri ◽  
Anuradha S G ◽  
Manga J ◽  
Deepak Karanam
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Supply Chain ◽  
Supply Chains ◽  
World Health Organization ◽  
World Wide ◽  
World Health ◽  
Future Supply ◽  
Entire World ◽  
Health Organization

An unanticipated outburst of pneumonia of inexperienced in Wuhan, , China stated in December 2019. World health organization has recognized pathogen and termed it COVID-19. COVID-19 turned out to be a severe urgency in the entire world. The influence of this viral syndrome is now an intensifying concern. Covid-19 has changed our mutual calculus of ambiguity. It is more world-wide in possibility, more deeply , and much more difficult than any catastrophe that countries and organizations have ever faced. The next normal requires challenging ambiguity head-on and building it into decision-making. It is examined that every entity involved in running supply chains would require through major as employee, product, facility protocols, and transport would have to be in place. It is an urgent need of structuring to apply the lessons well-read for our supply chain setup. With higher managers now being aware of the intrinsic hazards in their supply chain, key and suggestions-recommendations will help to guide leader to commit to a newly planned, more consistent supply chain setup. Besides, the employees’ mental health is also a great concern.

Segments Influencing Individual Investors Behavior And Their Investment Decision

2019 ◽  
Vol 118 (9) ◽  
pp. 154-160
Author(s):  
Dr. Kartikey Koti
Keyword(s):  
Decision Making ◽  
Social Factors ◽  
Stock Markets ◽  
Investment Decision ◽  
Individual Investors ◽  
Factors Affecting ◽  
The Social ◽  
Karnataka State ◽  
Essential Idea

The essential idea of this assessment is investigate the social factors affecting particular theorists' decisions making limit at Indian Stock Markets. In the examination coordinated standard of direct is Classified subject to two estimations the first is Heuristic (Decision making) and the resulting one is prospect.. For the assessment coordinated the data used is basic natured which is assembled through a sorted out survey from 100 individual money related authorities based out in Hubli and Dharwad city, Karnataka State in India on an accommodating way. The respondents were both sex and overwhelming part male were 68% . These theorists were having a spot with the age bundle between35-45 which is 38%. These respondents have completed their graduation were around 56%. These respondents had work inclusion of 5 to 10 years which is 45% and the majority of which were used in government portion which is 56%. Their compensation was between 4 to 6 Lakh and were fit for placing assets into business areas. The money related experts were widely masterminded placing assets into different portfolios like 32% in Share market and 20 % in Fixed store. These examiners mode to known various endeavor streets were through News, family and allies.  

The Paradox of Poverty: Socio-Economic Aspects of Population Growth.— By T. Scarlett Epstein and Darrell Jackson. The Macmillan of India Limited Delhi, 1975. pp.127.

1978 ◽  
Vol 17 (3) ◽  
pp. 380-382
Author(s):  
M. Javed Akbar Zaki
Keyword(s):  
Decision Making ◽  
Social Situation ◽  
Economic Security ◽  
Rural India ◽  
Factors Affecting ◽  
Number Of Children ◽  
Economic Progress ◽  
The Poor ◽  
Fertility Decision ◽  
The Social

To many social theoreticians, the population explosion, particularly in the developing nations presents a crippling threat to their developmental pro¬cesses. Their argument's validity rests mainly on the assumption that expected economic progress is swallowed up by unbalanced rise of numbers in the population. The book being reviewed deals mainly with this subject matter and is divided into two parts, each containing three articles contributed by various researchers. Part one, 'The Social context of Fertility Decision' is focused on analyzing the role of factors affecting fertility at the micro-level decision making process. The first article 'Fertility decision in rural India' by Vinod Jainath, examines the applicability to rural India of various models of the process of fertility decision making and finds most of these wanting with respect to the Indian social situation. While analyzing the fertility patterns of Rural India, he points out the positive need for larger families among the poor small farmers mainly due to labour supply considerations. The author argues that unemployment and under¬employment actually motivate the poor to have more children as it better ensures their economic security in their old age. As the chances of gaining employ¬ment for their offspring diminish, they are induced to increase the total number of children in order that atleast one will be able to support them. Thus a vicious circle of poverty arises in large families because of each of the parents wanting to increase their children's chances of employment by ultimately reducing the overall employment opportunities even further and exacerbating their poverty.

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