NDLI: Mining the Main Health Trend of the General Public based on Opinion Mining of Korean Blogsphere

Please wait, while we are loading the content...

Parsing Clinical Text: How Good are the State-of-the-Art Parsers?

Discriminatory Analysis of Alzheimer's Disease through pathway Activity inference in the Resting-State brain

Grounded Feature Selection for Biomedical Relation Extraction by the Combinative Approach

Entity Linking for Biomedical Literature

Inference of Disease E3s from Integrated Functional Relation Network

An Exploration of the Collaborative Networks for Clinical and Academic Domains in AIDS Research: A Spatial Scientometric Approach

Biomedical Named Entity Recognition Based on the Combination of Regional and Global Text Features

Identification of Coexpressed Gene Modules across Multiple Brain Diseases by a Biclustering Analysis on Integrated Gene Expression Data

A Display of Conceptual Structures in the Epidemiologic Literature

Injury Narrative Text Classification: A Preliminary Study

Identifying Cancer Subtypes based on Somatic Mutation Profile

Inferring Undiscovered Public Knowledge by Using Text Mining-driven Graph Model

Systematic Identification of Context-dependent Conflicting Information in Biological Pathways

Identification of Genomic Features in the Classification of Loss- and Gain-of-Function Mutation: [Extended Abstract]

Mining the Main Health Trend of the General Public based on Opinion Mining of Korean Blogsphere

Identification of a Specific Base Sequence of Pathogenic E. Coli through a Genomic Analysis

Integrative Database for Exploring Compound Combinations of Natural Products for Medical Effects

Mining Context-Specific Rules from the Literature for Virtual Human Model Simulation

Visualization of Zoomable Network for Multi-Compounds and Multi-Targets Analysis

Construction of Multi-level Networks Incorporating Molecule, Cell, Organ and Phenotype Properties for Drug-induced Phenotype Prediction

Detecting Phosphorylation Determined Active Protein Interaction Network during Cancer Development by Robust Network Component Analysis

TILD: A Strategy to Identify Cancer-related Genes Using Title Information in Literature Data

Mining the Main Health Trend of the General Public based on Opinion Mining of Korean Blogsphere

Content Provider	ACM Digital Library
Author	Jeong, Jaeseung Nam, Sang-Hyob Lee, Yong-il
Abstract	These days, social media usually becomes a reasonable standard for understanding the public's thought. Especially, people increasingly use internet media and SNS (twitter, facebook, blog, and etc.), to share opinions, news, advice, interests, moods, concerns, critics, facts, rumors, and everything. Therefore, public health research has been started a big change. Traditional public health study has depended on only regular clinical reports by health professionals. It is limited to practical use and general public has much difficulty to understand health information, even if it's his/her own information. Nowadays, over one billion people publish their ideas about many topics, including health conditions minute by minute. SNS provides researchers the freshest source of public health conditions on a global scale. Much of that data is public and available for mining. So this article pursues making an application of opinion mining for detecting the public's trend and finding valuable opinion among the massive information. The core of this research is analyzing the adjective of opinions. Our assumption is that many adjective expressions implicate deep and sincere meaning of its author. It is applicable for both low value postings filtering and tracking high value postings simultaneously. This approach is a simple and feasible criteria. The opinion mining process includes Korean morpheme analysis, opinion extraction, opinion tagging, positive / negative score evaluation. Our research's aim is to analyze Korean blog postings.
Starting Page	39
Ending Page	39
Page Count	1
File Format	PDF
ISBN	9781450312752
DOI	10.1145/2665970.2665985
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-11-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Text mining Sentiment analysis Machine learning Sentiment classification Opinion mining Public health
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Comprehensive Study on Lexicon-based Ensemble Classification Sentiment Analysis

Sentiment classification for Chinese reviews based on key substring features

Supervised polarity classification of Spanish tweets based on linguistic knowledge

A Survey on Sentiment Analysis for Web-Based Data by Using Various Machine Learning Techniques

On Multi-tier Sentiment Analysis Using Supervised Machine Learning

Web opinion mining based on sentiment phrase classification vector

Feature based opinion mining: A survey

Sentiment Analysis on Unstructured Review

A Sentiment-Based Hotel Review Summarization Using Machine Learning Techniques

Mining the Main Health Trend of the General Public based on Opinion Mining of Korean Blogsphere

Similar Documents

Comprehensive Study on Lexicon-based Ensemble Classification Sentiment Analysis

Sentiment classification for Chinese reviews based on key substring features

Supervised polarity classification of Spanish tweets based on linguistic knowledge

A Survey on Sentiment Analysis for Web-Based Data by Using Various Machine Learning Techniques

On Multi-tier Sentiment Analysis Using Supervised Machine Learning

Web opinion mining based on sentiment phrase classification vector

Feature based opinion mining: A survey

Sentiment Analysis on Unstructured Review

A Sentiment-Based Hotel Review Summarization Using Machine Learning Techniques

Mining the Main Health Trend of the General Public based on Opinion Mining of Korean Blogsphere