Online Social Support for Intimate Partner Violence Victims in China: Quantitative and Automatic Content Analysis

Tsz Hang Chu; Youzhen Su; Hanxiao Kong; Jingyuan SHI; Xiaohui Wang

doi:10.1177/1077801220911452

Online Social Support for Intimate Partner Violence Victims in China: Quantitative and Automatic Content Analysis

Tsz Hang Chu^*, Youzhen Su, Hanxiao Kong, Jingyuan SHI, Xiaohui Wang

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

15 Citations (Scopus)

Abstract

To examine the nature and content of messages presented in a popular Chinese online community about intimate partner violence (IPV), this study utilized a two-step analytic approach that combined quantitative content analysis and automatic content analysis. We collected 90,040 messages from the online community’s IPV group. Study 1 analyzed 8,343 randomly selected messages. The findings suggest that social support is commonly presented, while only a few messages expressed blame toward the victims. Study 2 analyzed the whole sample via machine learning technique and further showed that this online community was a space for the victims to obtain informational resources and emotional encouragement.

Original language	English
Pages (from-to)	339-358
Number of pages	20
Journal	Violence Against Women
Volume	27
Issue number	3-4
Early online date	27 Apr 2020
DOIs	https://doi.org/10.1177/1077801220911452
Publication status	Published - 1 Mar 2021

Scopus Subject Areas

Gender Studies
Sociology and Political Science
Law

User-Defined Keywords

content analysis
intimate partner violence
online social support

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1177/1077801220911452

Cite this

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title = "Online Social Support for Intimate Partner Violence Victims in China: Quantitative and Automatic Content Analysis",

abstract = "To examine the nature and content of messages presented in a popular Chinese online community about intimate partner violence (IPV), this study utilized a two-step analytic approach that combined quantitative content analysis and automatic content analysis. We collected 90,040 messages from the online community{\textquoteright}s IPV group. Study 1 analyzed 8,343 randomly selected messages. The findings suggest that social support is commonly presented, while only a few messages expressed blame toward the victims. Study 2 analyzed the whole sample via machine learning technique and further showed that this online community was a space for the victims to obtain informational resources and emotional encouragement.",

keywords = "content analysis, intimate partner violence, online social support",

author = "Chu, {Tsz Hang} and Youzhen Su and Hanxiao Kong and Jingyuan SHI and Xiaohui Wang",

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T1 - Online Social Support for Intimate Partner Violence Victims in China

T2 - Quantitative and Automatic Content Analysis

AU - Chu, Tsz Hang

AU - Su, Youzhen

AU - Kong, Hanxiao

AU - SHI, Jingyuan

AU - Wang, Xiaohui

PY - 2021/3/1

Y1 - 2021/3/1

N2 - To examine the nature and content of messages presented in a popular Chinese online community about intimate partner violence (IPV), this study utilized a two-step analytic approach that combined quantitative content analysis and automatic content analysis. We collected 90,040 messages from the online community’s IPV group. Study 1 analyzed 8,343 randomly selected messages. The findings suggest that social support is commonly presented, while only a few messages expressed blame toward the victims. Study 2 analyzed the whole sample via machine learning technique and further showed that this online community was a space for the victims to obtain informational resources and emotional encouragement.

AB - To examine the nature and content of messages presented in a popular Chinese online community about intimate partner violence (IPV), this study utilized a two-step analytic approach that combined quantitative content analysis and automatic content analysis. We collected 90,040 messages from the online community’s IPV group. Study 1 analyzed 8,343 randomly selected messages. The findings suggest that social support is commonly presented, while only a few messages expressed blame toward the victims. Study 2 analyzed the whole sample via machine learning technique and further showed that this online community was a space for the victims to obtain informational resources and emotional encouragement.

KW - content analysis

KW - intimate partner violence

KW - online social support

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M3 - Article

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SN - 1077-8012

VL - 27

SP - 339

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JO - Violence Against Women

JF - Violence Against Women

IS - 3-4

ER -

Online Social Support for Intimate Partner Violence Victims in China: Quantitative and Automatic Content Analysis

Abstract

Scopus Subject Areas

User-Defined Keywords

UN SDGs

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