Evidence map›Paper›PMID 39551926›Full record

ArticleHealthcare informatics research2024

Cancer-related Keywords in 2023: Insights from Text Mining of a Major Consumer Portal.

Wonjeong Jeong, Eunkyoung Song, Eunzi Jeong, Kyoung Hee Oh, Hye-Sun Lee, Jae Kwan Jun

Abstract read
In one paragraph

Article in Healthcare informatics research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Wonjeong JeongCancer Knowledge & Information Center, National Cancer Control Institute, National Cancer Center, Goyang, Korea.
Eunkyoung SongCancer Knowledge & Information Center, National Cancer Control Institute, National Cancer Center, Goyang, Korea.
Eunzi JeongCancer Knowledge & Information Center, National Cancer Control Institute, National Cancer Center, Goyang, Korea.
Kyoung Hee OhCancer Knowledge & Information Center, National Cancer Control Institute, National Cancer Center, Goyang, Korea.
Hye-Sun LeeCancer Knowledge & Information Center, National Cancer Control Institute, National Cancer Center, Goyang, Korea.
Jae Kwan JunCancer Knowledge & Information Center, National Cancer Control Institute, National Cancer Center, Goyang, Korea.

Funding

National Cancer Center 2410580-1
6 · The paper itself

Abstract

objectivesWith the growing importance of monitoring cancer patients' internet usage, there is an increasing need for technology that expands access to relevant information through text mining. This study analyzed internet articles from portal sites in 2023 to identify trends in the information available to cancer patients and to derive meaningful insights.

methodsThis study analyzed 19,578 news articles published on Naver, a major Korean portal site, from January 1, 2023, to December 31, 2023. Natural language processing, text mining, network analysis, and word cloud analysis were employed. The search term "am" (Korean for "cancer") was used to identify keywords related to cancer.

resultsIn 2023, an average of 1,631 cancer-related articles were published monthly, with a peak of 1,946 in September and a low of 1,371 in February. A total of 132,456 keywords were extracted, with "cure" (2,218 occurrences), "lung cancer" (1,652), and "breast cancer" (1,235) being the most frequent. Term frequency-inverse document frequency analysis ranked "struggle" (1064.172) as the most significant keyword, followed by "lung cancer" (839.988) and "breast cancer" (744.840). Network analysis revealed four distinct clusters focusing on treatment, celebrity-related issues, major cancer types, and cancer-causing factors.

conclusionsThe analysis of cancer-related keywords in 2023 indicates that news articles often prioritize gossip over essential information. These findings provide foundational data for future policy directions and strategies to address misinformation. This study underscores the importance of understanding the nature of cancer-related information consumed by the public and offers insights to guide official policies and healthcare practices.

Indexed as

Data MiningInformation DisseminationNatural Language ProcessingNeoplasmsNewspaper Article

Identifiers

PMID39551926
PMCPMC11570664

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.