scholarly journals Sentiment Analysis of Patients' Opinions in Healthcare using Lexicon-based Method

2019 ◽  
Vol 9 (1) ◽  
pp. 6977-6981
Keyword(s):  
Social Networking ◽  
Sentiment Analysis ◽  
Social Networking Sites ◽  
Healthcare Service ◽  
Opinion Mining ◽  
Research Area ◽  
Service Needs ◽  
Health Organizations ◽  
The World ◽  
New Research

The rapid increase in technology made people across the world use social networking sites to express their opinions on a topic, product or service. The success of a healthcare service directly depends on its users. If a majority of users like the service then it is a success otherwise, the service needs to be improvised. For improvising the service, the users' opinions need to be analyzed. Manually extracting and analyzing the content present on the web is a tedious task. This gave rise to a new research area called Sentiment Analysis. It is otherwise known as opinion mining. It is being used by many health organizations to make effective decisions on their service. This paper presents the sentiment analysis of patients' opinions on hospitals which is mainly used to improve healthcare service. This is implemented using a lexicon-based methodology to analyze the sentiment.

scholarly journals A Survey on Analysis of Twitter Opinion Mining Using Sentiment Analysis

2019 ◽  
pp. 537-542
Author(s):  
Vishnu VardanReddy ◽  
Mahesh Maila ◽  
Sai Sri Raghava ◽  
Yashwanth Avvaru ◽  
Sri. V. Koteswarao
Keyword(s):  
Social Networking ◽  
Sentiment Analysis ◽  
Social Networking Sites ◽  
Opinion Mining ◽  
Online Communication ◽  
Valuable Insight ◽  
Huge Amount ◽  
Twitter Data ◽  
Product Service ◽  
Different Types

In recent years, there is a rapid growth in online communication. There are many social networking sites and related mobile applications, and some more are still emerging. Huge amount of data is generated by these sites everyday and this data can be used as a source for various analysis purposes. Twitter is one of the most popular networking sites with millions of users. There are users with different views and varieties of reviews in the form of tweets are generated by them. Nowadays Opinion Mining has become an emerging topic of research due to lot of opinionated data available on Blogs & social networking sites. Tracking different types of opinions & summarizing them can provide valuable insight to different types of opinions to users who use Social networking sites to get reviews about any product, service or any topic. Analysis of opinions & its classification on the basis of polarity (positive, negative, neutral) is a challenging task. Lot of work has been done on sentiment analysis of twitter data and lot needs to be done. In this paper we discuss the levels, approaches of sentiment analysis, sentiment analysis of twitter data, existing tools available for sentiment analysis and the steps involved for same. Two approaches are discussed with an example which works on machine learning and lexicon based respectively.

Adoption of mobile social networking sites for learning?

2015 ◽  
Vol 39 (6) ◽  
pp. 762-778 ◽  
Author(s):  
Choy-Har Wong ◽  
Garry Wei-Han Tan ◽  
Siew-Phaik Loke ◽  
Keng-Boon Ooi
Keyword(s):  
Social Networking ◽  
Learning Community ◽  
Social Networking Sites ◽  
Structural Equation ◽  
Mobile Network ◽  
Research Area ◽  
Equation Modeling ◽  
Content Type ◽  
Mobile Social Networking ◽  
New Research

Purpose – The purpose of this paper is to explore the factors that influence users’ behavioral intention (BI) to adopt mobile social networking sites (mSNS) in facilitating formal/informal learning. Specifically, the study also investigates the association of mobility, reachability and convenience with performance expectancy (PE) and effort expectancy (EE). Design/methodology/approach – Partial least squares structural equation modeling (PLS-SEM) approach was applied to test on 266 valid responses. Findings – The findings indicated that learning compatibility (LC), PE, EE and copyright clearance (CC) has a significant effect on BI. The results also revealed that EE is influenced by mobility, reachability and convenience. PE however was found to be influenced by convenience. Practical implications – The results of this study provides valuable insights and references for practitioners and mobile network providers in developing mSNS in facilitating learning. Originality/value – While mSNS have the potential to become a new research area with numerous benefits for the learning community, there is little research on the adoption factors on mSNS in facilitating learning. This study therefore attempts to close the research gap by contributing to the mobile literatures.

scholarly journals A Inspection on Sentiment Research of Big Data: Techniques, Open Challenges

2019 ◽  
Vol 8 (6S4) ◽  
pp. 362-365
Keyword(s):  
Social Networking ◽  
Sentiment Analysis ◽  
Social Networking Sites ◽  
Opinion Mining ◽  
Service Industry ◽  
Research Work ◽  
Educational Institutions ◽  
Business Organizations ◽  
The Public ◽  
Day By Day

Due to the invention of Web 2.0, the users have become more interest to share their content day by day. The emergence of various social networking sites has added to a greater extent to these activities. These provide a very good platform for the users to share the opinions of the persons across the globe. The opinions shared by the customers on the web can have the prevalent over the service industry. Many industries such as educational institutions, researchers, business organizations are concentrating opinion mining which is also called as sentiment analysis (SA) to retrieve the views and opinions posted by the public. This paper made a survey on Sentiment Analysis (SA) which aims to discusses technical aspects of SA (techniques, types) .This paper further highlights the main challenges faced by SA. These challenges present a lot of scope for research work in the future

A Hybrid Multilingual Fuzzy-Based Approach to the Sentiment Analysis Problem Using SentiWordNet

2020 ◽  
Vol 28 (03) ◽  
pp. 361-390
Author(s):  
Youness Madani ◽  
Mohammed Erritali ◽  
Jamaa Bengourram ◽  
Francoise Sailhan
Keyword(s):  
Fuzzy Logic ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Opinion Mining ◽  
Hybrid Approach ◽  
Research Area ◽  
Hadoop Mapreduce ◽  
Hadoop Distributed File System ◽  
Active Research ◽  
New Research

Sentiment Analysis or in particular social network analysis (SNA) is a new research area which is increased explosively. This domain has become a very active research issue in data mining and natural language processing. Sentiment analysis (opinion mining) consists in analyzing and extracting emotions, opinions or attitudes from product’s reviews, movie's reviews, etc., and classify them into classes such as positive, negative and neutral, or extract the degree of importance (polarity). In this paper, we propose a new hybrid approach for classifying tweets into classes based on fuzzy logic and a lexicon based approach using SentiWordnet. Our approach consists in classifying tweets according to three classes: positive, negative or neutral, using SentiWordNet and the fuzzy logic with its three important steps: Fuzzification, Rule Inference/aggregation, and Defuzzification. The dataset of tweets to classify and the result of the classification are stored in the Hadoop Distributed File System (HDFS), and we use the Hadoop MapReduce for the application of our proposal.

The role of social networking sites in the revolution of 25 January 2011 Egyptian

2019 ◽  
Vol 2 (3) ◽  
pp. 1
Author(s):  
Qassim Alwan Saeed ◽  
Khairallah Sabhan Abdullah Al-Jubouri
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
Arab Spring ◽  
The World ◽  
The Revolution

Social media sites have recently gain an essential importance in the contemporary societies، actually، these sites isn't simply a personal or social tool of communication among people، its role had been expanded to become "political"، words such as "Facebook، Twitter and YouTube" are common words in political fields of our modern days since the uprisings of Arab spring، which sometimes called (Facebook revolutions) as a result of the major impact of these sites in broadcasting process of the revolution message over the world by organize and manage the revolution progresses in spite of the governmental ascendance and official prohibition.

scholarly journals Opinion Mining and Sentiment Analysis on Big Data

2020 ◽  
pp. 410-415
Author(s):  
Shruti Rajkumar Choudhary
Keyword(s):  
Artificial Intelligence ◽  
Social Networking ◽  
Sentiment Analysis ◽  
Text Analysis ◽  
Opinion Mining ◽  
Stock Exchange ◽  
Daily Basis ◽  
Text Data ◽  
The Public ◽  
Public Sentiment

<p>Opinion mining is extract subjective information from text data using tools such as NLP, text analysis etc. Automated opinion mining often uses machine learning, a type of artificial intelligence (AI), to mine text for sentiment. Opinion mining, which is also called sentiment analysis, involves building a system to collect and categorize opinions about a product.In this project the problem of sentiment analysis in twitter; that is classifying tweets according to the sentiment expressed in terms of positive, negative or neutral. Twitter is an online micro-blogging and social-networking platform which allows users to write short status updates of maximum length 140 characters. It is a rapidly expanding service with over 200 million registered users out of which 100 million are active users and half of them log on twitter on a daily basis - generating nearly 250 million tweets per day. Due to this large amount of usage we hope to achieve a reflection of public sentiment by analysing the sentiments expressed in the tweets. Analysing the public sentiment is important for many applications such as firms trying to find out the response of their products in the market, predicting political elections and predicting socioeconomic phenomena like stock exchange.</p>

A Study on the Internet Usage Pattern of Youths in Sikkim

2022 ◽  
pp. 109-121
Author(s):  
Saibal Kumar Saha ◽  
Sangita Saha
Keyword(s):  
Social Networking ◽  
Internet Addiction ◽  
Social Networking Sites ◽  
Internet Usage ◽  
The Internet ◽  
Usage Pattern ◽  
The World ◽  
Youth Population ◽  
Video Calling

Internet is being used by people all over the world. It has become a part of their day-to-day activity. The smartness brought by internet and its related devices have made life of people easy. Sharing knowledge, researching, and reaching out to people are now within the reach of fingertips. This study aims to find the internet usage pattern of youth in Sikkim, India. Fourteen internet activities have been identified and through a survey. The usage of these activities was analysed for the youth population in Sikkim, India. It has been found that, more or less, all the activities are used by the youth population of Sikkim. The most popular activity is use of emails and social networking sites while blogging and video calling is not too popular. In addition, it has been found that 67% of the users use internet for more than 3 hours per day. Hence, there also is a serious risk of “internet addiction.”

Network Text Analysis and Sentiment Analysis

2016 ◽  
pp. 137-153
Author(s):  
Veronica Ravaglia ◽  
Luca Zanazzi ◽  
Elvis Mazzoni
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Sentiment Analysis ◽  
Text Analysis ◽  
Social Networking Sites ◽  
Word Of Mouth ◽  
Network Text Analysis ◽  
Online Conversations ◽  
Web Forums

Through Social Media, like social networking sites, wikis, web forums or blogs, people can debate and influence each other. Due to this reason, the analysis of online conversations has been recognized to be relevant to organizations. In the chapter we introduce two strategic tools to monitor and analyze online conversations, Sentiment Text Analysis (STA) and Network Text Analysis (NTA). Finally, we propose one empirical example in which these tools are integrated to analyze Word-of-Mouth regarding products and services in the Digital Marketplace.

scholarly journals The value of social networking sites in hotels

2019 ◽  
Vol 22 (2) ◽  
pp. 114-132 ◽  
Author(s):  
Sarah Diffley ◽  
Patrick McCole
Keyword(s):  
Social Networking ◽  
Social Networking Sites ◽  
Customer Value ◽  
Hotel Industry ◽  
Research Area ◽  
Theory And Practice ◽  
Content Type ◽  
Marketing Activities ◽  
The Impact ◽  
Hotel Marketing

Purpose Despite the rapid growth of social networking sites (SNSs), research demonstrating the marketing application of these technologies is lacking. Consequently, this paper aims to explore the impact of SNSs on hotel marketing activities. Design/methodology/approach An exploratory study was used. Adopting a key informant approach, in-depth interviews were conducted with 14 respondents in the hotel industry, who use SNSs as part of their hotel marketing efforts. Findings Networked interactions facilitated by SNSs can influence the marketing activities of hotels in many ways. This extends to deeper connections and co-creating value with customers to enhance the market offerings and promotional activities of the firm. Not all interviewees capitalised upon the capabilities offered by SNSs. Practical implications SNSs act as a key knowledge resource that can be used by practitioners to create and deliver superior customer value. However, the extent to which this is achieved depends on who is responsible for implementing it. Specifically, those with a more proactive attitude and approach towards marketing on SNSs tend to reap greater benefits. Originality/value Using the service-dominant logic as a guide, this paper offers greater insight into the theory and practice of social media marketing in the hotel industry, an under-studied and fragmented research area.

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