Evidence map›Paper›PMID 35162845›Full record

ArticleInternational journal of environmental research and public health2022

How Do Chinese People View Cyberbullying? A Text Analysis Based on Social Media.

Shan Lu, Lingbo Zhao, Lizu Lai, Congrong Shi, Wanyue Jiang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

5 authors.

Shan LuKey Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Wuhan 430056, China.ORCID 0000-0002-7952-4143
Lingbo ZhaoDepartment of Applied Psychology, School of Humanities and Social Sciences, Fuzhou University, Fuzhou 350108, China.
Lizu LaiKey Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Wuhan 430056, China.
Congrong ShiKey Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Wuhan 430056, China.ORCID 0000-0002-4632-4874
Wanyue JiangKey Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Wuhan 430056, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rise of cyberbullying has been of great concern for the general public. This study aims to explore public attitudes towards cyberbullying on Chinese social media. Cognition and emotion are important components of attitude, and this study innovatively used text analysis to extract the cognition and emotion of the posts. We used a web crawler to collect 53,526 posts related to cyberbullying in Chinese on Sina Weibo in a month, where emotions were detected using the software "Text Mind", a Chinese linguistic psychological text analysis system, and the content analysis was performed using the Latent Dirichlet Allocation topic model. Sentiment analysis showed the frequency of negative emotion words was the highest in the posts; the frequency of anger, anxiety, and sadness words decreased in turn. The topic model analysis identified three common topics about cyberbullying: critiques on cyberbullying and support for its victims, rational expressions of anger and celebrity worship, and calls for further control. In summary, this study quantitatively reveals the negative attitudes of the Chinese public toward cyberbullying and conveys specific public concerns via three common topics. This will help us to better understand the demands of the Chinese public so that targeted support can be proposed to curb cyberbullying.

Indexed as

COVID-19CyberbullyingSocial MediaChinaHumansSARS-CoV-2attitudecyberbullyingsentiment analysissocial mediatext analysistopic model

Identifiers

PMID35162845
PMCPMC8834686

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.