Evidence map›Paper›PMID 40718572›Full record

ArticleAsia-Pacific journal of oncology nursing2025

Characterizing authoritative oncology-related key opinion leaders on Weibo: A social media profiling study.

Yiwen Duan, Yi Chen, Qi Sun, Jialin Chen, Jiaojiao Zhang, Bei Yun, Tingting Cai, Changrong Yuan

Abstract read
In one paragraph

Article in Asia-Pacific journal of oncology nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

8 authors.

Yiwen DuanSchool of Nursing, Fudan University, Shanghai, China.
Yi ChenSchool of Nursing, Fudan University, Shanghai, China.
Qi SunSchool of Nursing, Fudan University, Shanghai, China.
Jialin ChenSchool of Nursing, Fudan University, Shanghai, China.
Jiaojiao ZhangSchool of Nursing, Fudan University, Shanghai, China.
Bei YunSchool of Nursing, Fudan University, Shanghai, China.
Tingting CaiSchool of Nursing, Fudan University, Shanghai, China.
Changrong YuanSchool of Nursing, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to explore the heterogeneity of authoritative oncology-related key opinion leaders (AOKOLs) on Weibo and to develop their user profiles that support precise health information dissemination and personalized online patient support. Methods: Using Python-based web scraping, data were collected from Weibo (Nov 2023-Nov 2024) based on six oncology-related keywords. AOKOLs were profiled using K-means clustering across 12 indicators in four dimensions: content output, interaction, professional background, and social network features. Sentiment analysis of representative user comments was conducted to assess audience emotional responses. Results: A total of 143 AOKOLs were included through clustering analysis, with 89,118 posts and 837,602 comments collected from their Weibo accounts. These AOKOLs were categorized into four distinct digital influence profiles: 31 expert knowledge communicators, 47 science information sharers, 47 emotional support providers, and 18 social engagement facilitators. These groups differed in content focus, engagement patterns, and audience interaction. Sentiment analysis of 62,154 comments from 37 representative AOKOLs revealed varying emotional responses across profiles, highlighting their differential impacts on audience well-being and digital health communication. Conclusions: This study reveals distinct user profiles of AOKOLs on Weibo, highlighting the diverse communication strategies, engagement styles, and emotional influences within digital health ecosystems. Findings offer insights into how digital influencers can support patient-centered care and enhance quality of life through intelligent health communication.

Indexed as

Clustering analysisKey opinion leadersOnline health communitiesSentiment analysisSocial mediaUser profiling

Identifiers

PMID40718572
PMCPMC12296463

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.