About: Analysis of Women’s Health Online News Articles Using Topic Modeling

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Analysis of Women’s Health Online News Articles Using Topic Modeling Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Analysis of Women’s Health Online News Articles Using Topic Modeling
Creator	Cho, Kyoung Kim, Shine Woo, Young
Source	Medline; PMC
abstract	OBJECTIVES: This research aimed to understand the popularity of topics in the field of women’s health through analysis of online news articles which were chronologically classified and examined to determine how women’s health and diseases had changed over time. METHODS: Women’s health and disease news articles were collated from a popular news website between 1993 to 2015 and preprocessed using gynecological medical terminology, Korean words and nouns (excluding general nouns not related to women’s healthcare topics). The resultant articles (N = 7,710) were analyzed using the Latent Dirichlet Allocation algorithm and major topics were extracted. Topic trends were analyzed by year and period for women’s health. RESULTS: It was observed that most of the women’s health articles were focused on “Healthcare”, and 9 other topics were identified that represented a relatively small proportion in 1993–2000. In 2001–2005, most of the articles were focused on “Medical Services” and “Dietary Supplements” with some specific topics that peaked people’s interest, as compared to those focused on “Healthcare” in the 1990s. It was also observed that differences in the proportion of each topic was small after 2011. CONCLUSION: Changes in topics related to women’s disease were not clearly distinguished in the 1990s but this changed from 2001where articles related to “women disease” appeared as articles on the topics of various diseases.
has issue date	2019-06-01(xsd:dateTime)
bibo:doi	10.24171/j.phrp.2019.10.3.07
bibo:pmid	31263665
has license	cc-by-nc-nd
sha1sum (hex)	eb7432cee2519eefd1a6672e1f0bc483c9527a8d
schema:url	https://doi.org/10.24171/j.phrp.2019.10.3.07
resource representing a document's title	Analysis of Women’s Health Online News Articles Using Topic Modeling
has PubMed Central identifier	PMC6590882
has PubMed identifier	31263665
schema:publication	Osong Public Health Res Perspect
resource representing a document's body	covid:eb7432cee2519eefd1a6672e1f0bc483c9527a8d#body_text
is schema:about of	named entity 'HOMEPAGE' named entity '27S' named entity 'TOPIC' named entity 'HTTP' named entity 'NEWS' named entity 'HISTORY' named entity 'ARTICLE' named entity 'JOURNAL ' named entity 'PUBLIC HEALTH' named entity 'RESEARCH' named entity 'ANALYSIS' named entity 'USING' named entity 'ORG' named entity 'ONLINE' named entity 'MODELING' named entity 'WOMEN' named entity 'HEALTH' named entity 'Topic Modeling' named entity 'suicide prevention' named entity 'cerebrovascular disease' named entity 'Support Vector Machine' named entity 'data mining' named entity 'topic modeling' named entity 'high heel' named entity 'morpheme' named entity 'Twitter' named entity 'topic modeling' named entity 'protein' named entity 'topic modeling' named entity 'childbirth' named entity 'hepatitis' named entity 'mental health' named entity 'symptom' named entity 'social issues' named entity 'arthropathy' named entity 'calcium' named entity '8,000' named entity 'muscle' named entity 'Topic modeling' named entity 'lung cancer' named entity 'dementia' named entity 'cholesterol' named entity 'protein' named entity 'women's health' named entity 'breast implants' named entity 'dietary supplement' named entity 'women's health' named entity 'health issues' named entity 'alcohol' named entity 'vitamin' named entity 'varicose vein' named entity 'thyroid disease' named entity 'kidney disease' named entity 'women's health' named entity 'data mining' named entity 'dietary supplement' named entity 'healthcare services' named entity 'menopause' named entity 'topic modeling' named entity 'symptom' named entity 'kidney disease' named entity 'probability' named entity 'allergy' named entity 'stroke' named entity 'breast cancer' named entity 'blood circulation' named entity 'file format' named entity 'childbirth' named entity 'hair loss' named entity 'foot health' named entity 'dietary supplement' named entity 'headache' named entity 'big data' named entity 'acquired immunodeficiency syndrome' named entity 'dietary supplement' named entity 'social network services' named entity 'nutrient' named entity 'Middle East Respiratory Syndrome' named entity 'big data'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software