Please summarize the following article. Has to be TWO pages.
King-wa Fu et al.: Attempted
Crisis©2013;
Suicide
2013 Vol.
Hogrefe
on34(6):406–412
a Microblog
Publishing
Research Trends
Responses to a Self-Presented
Suicide Attempt in Social Media
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
A Social Network Analysis
King-wa Fu1, Qijin Cheng2, Paul W.C. Wong3, and Paul S. F. Yip4
1
Journalism and Media Studies Centre, University of Hong Kong, Hong Kong, China, 2Department of
Psychiatry, University of Rochester Medical Center, NY, USA 3HKJC Centre for Suicide Research and
Prevention, University of Hong Kong, China, 4Department of Social Work and Social Administration,
University of Hong Kong, Hong Kong, China
Abstract. Background: The self-presentation of suicidal acts in social media has become a public health concern. Aims: This article
centers on a Chinese microblogger who posted a wrist-cutting picture that was widely circulated in Chinese social media in 2011. This
exploratory study examines written reactions of a group of Chinese microbloggers exposed to the post containing a self-harming message
and photo. In addition, we investigate the pattern of information diffusion via a social network. Methods: We systematically collected
and analyzed 5,971 generated microblogs and the network of information diffusion. Results: We found that a significant portion of written
responses (36.6%) could help vulnerable netizens by providing peer-support and calls for help. These responses were reposted and
diffused via an online social network with markedly more clusters of users – and at a faster pace – than a set of randomly generated
networks. Conclusions: We conclude that social media can be a double-edged sword: While it may contagiously affect others by spreading
suicidal thoughts and acts, it may also play a positive role by assisting people at risk for suicide, providing rescue or support. More
research is needed to learn how suicidally vulnerable people interact with online suicide information, and how we can effectively intervene.
Keywords: attempted suicide, microblog, China, social network analysis, social media
Digital technologies and the recent development of the Internet have given rise to Web 2.0 (Oreilly, 2007) and a multitude of social media (Kaplan & Haenlein, 2010) applications (e.g., Wikipedia, YouTube, blogs, microblogs [Twitter or Sina Weibo in China], and social networking sites
[Facebook/MySpace or Renren in China]). These Internet
applications depart from the conventional static and noninteractive Internet sites and enable online users to create
user-generated content, participate in collaborative projects, and interact and connect with their social network in
real time. Social media not only enrich the content and
scope of personal communication, it also facilitates uninhibited communication and selective self-presentation of
undesirable behavior (Kaplan & Haenlein, 2010). From a
research perspective, social media can provide an excellent
platform for collecting data and studying human behaviors,
especially rare behaviors such as suicide and suicide prevention (Cheng, Chang, & Yip, 2012).
The association between social media and suicide has
recently become a public health concern (Luxton, June, &
Crisis 2013; Vol. 34(6):406–412
DOI: 10.1027/0227-5910/a000221
Fairall, 2012). Studies on suicide and the Internet emerged
about a decade ago (Fu, Wong, & Yip, 2009). Several lines
of inquiry have formed, with one line focused on how information about suicide methods or communication is
spread through the Internet (eventually negatively impacting suicidal behavior; Fu et al., 2009; Rajagopal, 2004;
Ruder, Hatch, Ampanozi, Thali, & Fischer, 2011). Another
line investigates the extent to which various types of suicide-related information are accessible on the Internet
(Biddle, Donovan, Hawton, Kapur, & Gunnell, 2008;
Cheng, Fu, & Yip, 2011; Recupero, Harms, & Noble, 2008;
Wong et al., 2013). The third line examines whether an
individual’s suicidal ideation is linked to Internet addiction
symptoms (Fu, Chan, Wong, & Yip, 2010).
One important, yet understudied, research area is how
social media affect people’s communication about suicide.
Suicidal people often communicate with ambiguity, being
in a state between dying by killing oneself and seeking the
attention and help of others (Farberow & Shneidman,
1961). However, the pattern of suicide communication may
© 2013 Hogrefe Publishing
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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
King-wa Fu et al.: Attempted Suicide on a Microblog
have actually changed with the advent of the Internet. Vygotsky (1978) long argued that communication tools allow
for the extension of human capabilities. Communication
tools include traditional analog (e.g., pens, telegraph, telephone) and digital forms, the latter having upended our traditional ways of communication. It is therefore important
to investigate how computer-mediated communication differs from nonmediated or face-to-face communication with
respect to the psychological processes and outcomes. Several general approaches or theories have been developed to
conceptualize computer-mediated communication (Walther, 2011). For example, the hyperpersonal model presumes that an individual’s online self-presentation can be
a form of personal impression and relationship management that has capabilities far exceeding face-to-face communication (Walther, 1996). Through a channel of reduced
communication cues and asynchronous interaction, Internet message senders may selectively present themselves in
ways “that are more stereotypically desirable in achieving
their social goals” (Walther, 1996, p. 28), such as managing
a desirable personal image or building intimacy. On the
receiving end, message receivers opt to idealize the sender
and to “build stereotypical impressions of their partners
with qualifying the strength of such impressions in light of
the meager information” (Walther, 1996, p. 29). In the context of a suicidal act, because of their capacity to enable
self-disclosure of uninhibited behavior social media may
lower the threshold of vulnerable and suicidal people. Consequently, such people may be more apt to present selfharm intentions or behaviors to a network of people, including both close friends and loose acquaintances. In the
context of suicide communication, the hyperpersonal model posits that the intentions of suicidal individuals to selfharm are uninhibited in social media by allowing them to
selectively present themselves crying out for help. On the
receiving end, decoders have to rely on limited communication cues and personal attitudes to respond to such signals.
As of March 2013, over 200 million active Twitter user
accounts are generating over 400 million tweets every day
(Wickre, 2013). Although Twitter is not accessible in China, local microblogging sites, like Sina Weibo and Tencent
Weibo, have rapidly grown on their own to become major
channels for Chinese Internet users to read, write, communicate, and forward 140-character messages via a variety
of technology platforms. These two leading microblogging
service providers in China each claim their registered account base reached 500 million at the end of 2012 (Mozur,
2013). According to CNNIC (China Internet Network Information Center, 2012), the total number of Chinese microbloggers reached 274 million by mid-2012, comprising
51% of the total Internet users in China. The total number
of microbloggers is estimated to reach 400 million by the
end of 2014 (iResearch, 2011). As Western media put it,
microblogging has emerged to become one of the major
“free-speech platforms” in China (Richburg, 2011). This
new medium gives Chinese Internet users unprecedented
© 2013 Hogrefe Publishing
407
opportunities for sharing information as well as expressing
opinions and emotions, thereby serving as “We the Media”
(Gillmor, 2004).
This study is purposely exploratory. We seek to investigate the consequences of presenting self-harm behavior
through social media. Using a case study in China, we address the following questions: (1) How do Chinese microbloggers respond to the self-presentation of self-harm behavior? (2) How are such microblog posts propagated in a
social network? and (3) What are the implications for suicide prevention?
Method
Quantitative content analysis was conducted to study a selfharm entry in a microblog in China. On February 23, 2011,
at 9:56 pm, a wrist-cutting photo was posted on Sina Weibo
by a user J, whose account profile indicated he was a male
living in Shenzhen city. This microblog read, “Today, I returned back to you. That’s all. You made me feel like falling
from heaven to hell. Now I get it.” Once published, the post
and the picture attached were broadly circulated on the microblog system. About 3 hours later, another message posted by User J read, “Sorry, I am so sorry. I didn’t know my
personal issue could draw so much attention here. I am fine.
I have already wrapped up my wound.” According to media
reports on February 25, 2011, the police confirmed User J’s
real identity and his suicidal act.
On the Sina Weibo platform, users can respond to a post
by two different means: reposting or commenting. When
reposting, a microblogger adds a remark and sends the original post to his or her followers. A microblogger can also
respond by commenting on the original post. In the case of
user J’s weibo, the original post was reposted 3,974 times
and received 1,997 comments by 3,696 microbloggers
within 3 hours (as of February 24, 1:05 am), yielding 5,971
microblog pieces of content that we collected and analyzed.
We used the Application Programming Interface (API)
provided by Sina Weibo to gather reposts and comments
on March 15, 2011. Reposters’ self-reported sex, follower
counts, friend counts, and provinces of origin were also
collected. One thousand randomly generated 10-digit user
identity codes served as control subjects to represent the
overall microblogger population.
In addition, user names contained in the reposts were
extracted. When a microblog is reposted, a reference in the
format of “//@screen_name,” where screen_name is the
displayed user name, is offered by default at the beginning
of the reposting text and is preserved in its entirety if not
deleted by the author. We took advantage of this property
to trace the pattern of reposting.
To generate a coding framework, the first author analyzed collected reposts and comments inductively, and then
classified and regrouped them into an initial category
framework. Two native Chinese coders were recruited to
Crisis 2013; Vol. 34(6):406–412
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408
King-wa Fu et al.: Attempted Suicide on a Microblog
conduct the classification. After a training session, the coders provided feedback in a subsequent review meeting. The
categories were amended accordingly and the final coding
framework was developed. Next, 100 posts were randomly
selected from the dataset and coded by two coders in a
parallel and independent manner to assess intercoder reliability. The κ coefficient of the classification was 0.66,
which can be considered to be substantial agreement (Landis & Koch, 1977). Finally, one coder completed the coding
of the entire dataset using the coding framework.
Interconnections (e.g., a link between two nodes signified a repost sent from one microblogger to another) between microbloggers are represented by a directed social
graph. To analyze the graph, we used R version 2.12.1 (R
Development Core Team, 2010). Specifically, we used the
network research package igraph (Csardi & Nepusz, 2006)
to conduct social network analysis, evaluating the nodelevel parameters (e.g., in-degree, out-degree, and betweenness centrality measures), which are used to represent the
importance of each individual microblogger in a network
(Freeman, 1978). For example, the out-degree centrality of
a microblogger M means the number of other microbloggers who repost M’s message. The in-degree centrality of
M represents the frequency with which M reposts messages
received from others. The betweenness centrality of M represents the total count of pairs of nodes whose shortest path
between them consists of M, thereby denoting the relative
importance of the position M has in the network. Moreover,
network-level topological parameters, including average
pathlength and global cluster coefficient, were deployed to
compare different networks (Lewis, 2009). The average
pathlength of a network is equal to the average number of
shortest paths over all direct paths connected between
nodes in that network. The global cluster coefficient is an
indicator of the extent to which the nodes of a network
cluster together. Fuchterman and Rheingold’s graph layout
algorithm (R’s igraph package) was used to visualize the
network. Moreover, a set of social graphs was randomly
generated using the Erdos-Renyi model (Csardi & Nepusz,
2006), a common approach for social network comparison
(Chau & Xu, 2007).
mation diffusion took a shorter distance on average to propagate the message from one node to the others. The larger
global cluster coefficient of the repost graph reflects the
existence of many relatively isolated and densely-knit user
clusters in the network.
A total of 3,696 microbloggers reposted the message;
Table 3 shows their self-reported sex, locations, and follower and friend counts. Compared to the random sample
obtained from the microblogger population, the data show
that people who contributed to reposting were more likely
to come from cities in China that are economically well
developed and top ranked in GDP per capita (National Bureau of Statistics of China, 2012). The five top ranked cities
were Shanghai (1st ranked in GDP per capita, the same as
below), Beijing (2nd), Jiangsu (4th), Zhejiang (5th), and
Guangdong (7th). In addition, these reposters had a higher
likelihood of having more than 1,000 followers and 200
friends.
Table 1. Classification of microbloggers’ responses to the
original message (N = 5,971)
Type of response
%
Translated examples
Caring, showing empa- 19.8
thy, and giving advice
“Are you alright? Hope you are
fine.”
“Brother, I wish you are ok.”
“Don’t . . . Life is so important. If
you give up your life, you lose your
love too.”
Calling for help
16.8
“Damn it. Call the police now. He is
in Shenzhen.”
“110, 120, SOS . . . Help this guy.”
“My God. Who knows his address?
Call emergency now.”
Cynical or indifferent
comments
23.4
“Why make your hand full of chocolate?”
“Save your blood. Many hospitals
need that.”
“[Angry] I hate these self-harmers.”
Shocked
19.5
“OMG. So scary!!”
“What’s up? You scare me!!”
“Ah! Live Weibo broadcast of suicide at midnight?”
Forward to others with 20.4
no comment
Reposting Weibo post
Results
In total 5,971 microblogs were collected and analyzed. Table 1 shows the categories of the microbloggers’ written
reactions. Among the collected microblogs, 36.6% concerned caring, showing empathy, and calling for help (see
examples in Table 1), 23.4% evidenced a negative attitude
(i.e., cynical or indifferent comments), 19.5% were emotional presentations of shock, and 20.4% were merely reposts.
Table 2 demonstrates that the repost graph evidenced a
slightly shorter average path length than the group average
of the randomly generated graphs, indicating that its inforCrisis 2013; Vol. 34(6):406–412
Table 2. Comparisons between the repost graph and the
randomly generated graphs
Repost graph
Random graphs
Number of nodes
3,696
3,696
Number of edges
1,813
1,813
–4
Density
1.33 × 10
1.33 × 10–4
Average degree
0.981
0.981
Average path length
1.93
1.96
2.9 × 10–4
Global cluster coefficient
4.92 × 10–3
Note. Random graph indicators were obtained by calculating mean
values from 30 randomly generated graphs.
© 2013 Hogrefe Publishing
King-wa Fu et al.: Attempted Suicide on a Microblog
409
Table 3. Characteristics of reposters
Characteristics Categories
Reposters
sample
(N = 3,696)
Frequency (%)
Random
samples
(N = 1,000)
Frequency (%)
Sex
Male
54.4
55.0
Female
42.8
44.9
Not mentioned
2.8
0.1
Guangdong
26.7
15.1
Peking
16.4
4.3
Shanghai
9.7
3.7
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Location
Zhejiang
3.3
4.2
Jiangsu
3.6
5.8
International
3.3
1.1
Others
3.4
7.3
Sichuan
3.3
4.4
Fujian
2.3
4.5
Hubei
1.2
2.8
Other provinces 26.8
46.8
No. of followers 0–999
No. of friends
90.3
100.0
1,000–1,999
5.0
0
2,000–2,999
1.7
0
3,000–3,999
0.6
0
4,000–4,999
0.4
0
≥ 5,000
2.0
0
0–199
52.7
99.0
200–399
24.6
0.8
400–599
8.7
0.2
600–799
4.5
0
800–999
2.8
0
Figure 1. Graphical visualization of the repost network.
Note. Each node represents a microblogger, and an arrow
represents a message reposted from one microblogger to
the other. The nodes with name labels are the top ten most
influential reposters.
In Table 4, bloggers J1 to J10 denote the top ten most
influential microbloggers who participated in reposting the
original weibo. They were ranked by their betweenness
centrality, an indicator of its importance in the network of
information diffusion. None of the top ten microbloggers
made cynical or indifferent comments. Figure 1 is a graphical visualization of the information diffusion, indicating
how the reposters were intercommunicated. As seen in Figure 1, the major reposters were often positioned at cluster
locations of the network and linked with a large number of
other reposters.
Table 4. Characteristics of the 10 most influential microbloggers who reposted the original message
Name of blogger
Sex
Type*
Time reposted
No. followers
Out degree**
In degree**
Betweenness**
Blogger J1
F
2
22:17:54
4,075
11
3
108
Blogger J2
F
2
22:17:56
12,795
7
1
80
Blogger J3
F
4
22:17:51
655
4
1
64
Blogger J4
F
4
22:17:38
462
2
1
57
Blogger J5
F
5
22:17:26
268
19
1
52
Blogger J6
F
4
22:17:51
801
4
1
51
Blogger J7
M
1
22:17:50
2,067
4
1
48
Blogger J8
F
5
22:17:50
829
5
1
44
Blogger J9
M
2
22:18:13
6,447
37
3
44
Blogger J10
F
4
22:17:45
691
10
1
43
Note. *Type of response: (1) “Caring, showing empathy, and giving advice”; (2) “Calling for help”; (3) “Cynical or indifferent comments”; (4)
“Shocked”; and (5) “Only reposting with no comment.” **Out-degree centrality of a microblogger M means the number of other microbloggers
who repost M’s message. In-degree centrality of M represents the frequency that M reposts the message received from others. Betweenness
centrality of M represents the total count of pairs of nodes whose shortest path between them consists of M, denoting the relative importance
of the position where M is located in the network.
© 2013 Hogrefe Publishing
Crisis 2013; Vol. 34(6):406–412
410
King-wa Fu et al.: Attempted Suicide on a Microblog
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Discussion
This exploratory study indicates that there were various
types of responses from Chinese microbloggers to an individual’s online presentation of self-harm. A significant portion of the responses appeared to be positive, characterized
functionally by efforts of caregiving and offers of assistance to the call for help. The top 10 most influential microbloggers who reposted the original message showed
concern and care for the person who self-harmed. Drawing
on the hyperpersonal model (Walther, 1996), the consequence of these caregiving responses may positively address and reinforce a suicidal individual’s underlying goal
of self-presentation: the cry for help (Farberow & Shneidman, 1961).
Although media presentation of suicide is often considered harmful to vulnerable suicidal people (Niederkrotenthaler et al., 2012), and suicide-related communication
within a cluster may be contagious (Joiner, 1999), this
study and others (Ruder et al., 2011; Silenzio et al., 2009)
suggest a potential positive function of social media in suicide prevention. Specifically, diffusion of messages about
one’s suicidal thoughts or behaviors on social media may
serve as an early identification tool and as a rescuing platform for those who are at suicidal risk or a strategy of engaging socially isolated individuals. For instance, Facebook has launched a number of initiatives to assist users in
identifying others who exhibit suicidal tendencies (Ruder
et al., 2011). Our findings, like those of others, suggest that
online media can also be constructively utilized to detect
individuals with suicidal risks earlier, thereby ensuring a
speedy and timely rescue. Increasing amounts of supporting empirical evidence prompt us to wonder if it is necessary to reexamine the suicide reporting guidelines in the
international media, especially given the special nature of
online social media. Perhaps new guidelines should be developed specifically for online service and information providers.
Furthermore, our social network analysis shows that
there were more user clusters in the repost network (i.e.,
larger cluster coefficient) than in the random network, and
that the speed of information diffusion was faster (i.e.,
shorter average pathlength), suggesting that a repost network can be activated quickly for effective communication
in emergency situations. It also suggests that loose acquaintances, known as “weak ties” (Granovetter, 1973), might
be more helpful than a closed group within an interpersonal
network in terms of responding to emergencies such as suicide attempts. Recent studies on social media information
diffusion demonstrate that removing weak ties from the
network considerably decreases the effectiveness of information diffusion (Zhao, Wu, & Xu, 2010). A weak-ties network via social media may therefore effectively contribute
to the early identification of people at risk from the population at large. Therefore, if suicide prevention professionals or organizations can build up an online social media
Crisis 2013; Vol. 34(6):406–412
platform, it would be helpful to build up a network of gatekeepers or spectators who are able to contribute to early
identification of people at risk from the population at large.
Most influential reposters could serve as suicide prevention gatekeepers: They are more likely to show caring attitudes toward the attempter. Given the assumption that the
selected incident is not an isolated case, and the reactions
of the reposters are indeed common, suicide-prevention
professionals may consider developing awareness campaigns and gatekeeper training programs that target active
and popular online users.
Meanwhile, we acknowledge that it is still premature to
conclude that engaging with online social networks eventually reduces an individuals’ suicide risk (or at a minimum
does no harm). In this specific case, 20% of the messages
expressed a cynical or indifferent attitude toward the suicidal person’s self-presentation, with some considered cyberbullying. Disconfirmation may have undesirable effects
on the emotions of the attempter and other suicidal individuals who are exposed to these messages. This phenomenon
may be more pronounced if the post belongs to a celebrity,
much like the prominent impact of media reports of celebrity suicide (Fu & Yip, 2009). In addition, we do not know
whether the suicidal person received any proper help or
support from professionals and/or his offline social network after being found by the police, given that mental
health services are generally not very accessible in China
(Cheng et al., 2012). From the written responses, we could
not find any microbloggers exhibiting suicidal risks when
receiving and/or forwarding J’s message, but we remain
uncertain whether readers’ mental well-being would be impacted over a longer period of time. Online self-presentation may have other side effects not examined in the current
study.
The Chinese government recently imposed a legal requirement of using one’s real name when registering to use
social media (Bradsher, 2012). Early evidence suggests this
has had a chilling effect on political comments in China
(Fu, Chan, & Chau, 2013). Such a requirement may also
discourage vulnerable individuals’ expressions of feelings
or calls for help. The impact on the behavior of microbloggers is yet to be recognized, with more studies needed in
order to understand the requirement’s effect on the microblog usage in China.
Conclusion
Diffusion of suicide-related content across social media is
a recent and rapidly growing phenomenon. There are not
enough empirical data to suggest whether the benefits or
harms brought by social media on suicidality outweigh one
another. This study, however, suggests a suicidal attempt
can be disrupted in time if social media is harnessed in
positive ways. Researchers should closely monitor the effects of new media on individuals’ mental health and sui© 2013 Hogrefe Publishing
This document is copyrighted by the American Psychological Association or one of its allied publishers.
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King-wa Fu et al.: Attempted Suicide on a Microblog
cidal acts. Clinicians who help suicidal individuals should
explore their clients’ use of social media and suggest ways
to make social media one of the safety nets available to
them when necessary. Moreover, an appropriate referral
system needs to be established to provide follow-up support and services to individuals who self-present suicidal
thoughts and/or behaviors online. Suicide researchers
should closely monitor the potential effect of the new media on individual’s mental well-being and suicidality. Understanding how and why new information technologies
are adopted marks important research areas. Public health
and media professionals may consider developing guidelines to respond to this exploding phenomenon. Social media can be known as a double-edged sword: On the one
hand, it is a platform for spreading suicidal thoughts or
mimicking suicidal acts, whereas on the other hand it also
plays a constructive role in early detection of people at suicidal risk. Further empirical research is needed to reveal
how the suicidal population interacts with the social media
and what we can do to intervene effectively.
Acknowledgments
The authors wish to acknowledge Chrissy Yu and Alison
Hui for their assistance in data collection and coding of the
Internet content, and Helen Ma for her effort in editing the
manuscript. Qijin Cheng’s work is partially supported by a
Public Policy Research grant (HKU 70330-PPR-12) and a
grant from the Fogarty International Center of NIH, USA
(D43 TW009101).
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About the authors
Received September 18, 2012
Revision received April 3, 2013
Accepted April 8, 2013
Published online July 26, 2013
Journalism and Media Studies Centre
The University of Hong Kong
Pokfulam, Hong Kong
China
Tel. +852 3917-1643
Fax +852 2858-8736
E-mail kwfu@hku.hk
Crisis 2013; Vol. 34(6):406–412
Dr. King-wa Fu is an Assistant Professor at the Journalism and
Media Studies Centre (JMSC), The University of Hong Kong
(Hong Kong SAR). His research interests include political participation and media use, mental health/suicide and the media, health
communication, young people’s Internet use, and computational
method for media studies.
Dr. Qijin Cheng is a Postdoctoral Fellow at Department of Psychiatry, University of Rochester Medical Center, Rochester, NY,
USA as well as at HKJC Centre for Suicide Research and Prevention, the University of Hong Kong (Hong Kong SAR). Her research focuses on suicide, media, and social context.
Dr. Paul Wong, DPsyc (Clinical), is Assistant Professor at the
Department of Social Work and Social Administration, University
of Hong Kong (Hong Kong SAR). He is a National Representative of the International Association of Suicide Prevention. His
research interests include aborted suicide attempt, postvention,
homicide-suicide, Internet and suicide, and evaluation of suicide
prevention programs.
Prof. Paul Yip is Director of the Centre for Suicide Research and
Prevention and a professor at the Social Work and Social Administration Department, University of Hong Kong (Hong Kong
SAR). He is the recipient of Stengel Researcher’s Award (2011)
of the International Association of Suicide Prevention. His interests lie in adopting a public health approach for suicide prevention
and population health studies.
Dr. King-wa Fu
© 2013 Hogrefe Publishing
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