Ang Li1,2, Xiaoxiao Huang3, Dongdong Jiao4, Bridianne O'Dea2, Tingshao Zhu3, Helen Christensen2. 1. Department of Psychology, Beijing Forestry University, Beijing, China. 2. Black Dog Institute, University of New South Wales, Sydney, Australia. 3. Institute of Psychology, Chinese Academy of Sciences, Beijing, China. 4. National Computer System Engineering Research Institute of China, Beijing, China.
Abstract
INTRODUCTION: Broadcasting a suicide attempt on social media has become a public concern in China. Stigmatizing attitudes around such broadcast can limit help-seeking and increase the likelihood of death. To reduce stigmatizing attitudes, this paper aims to detect stigma expressions in social media posts through language use patterns and then identify suicide literacy in responses to such broadcast. METHODS: Firstly, to examine linguistic patterns of stigma expressions, 6632 Weibo posts with keywords were collected and analyzed. Using 102 linguistic features, 2 classification models were built: one for differentiating between stigmatizing and nonstigmatizing attitudes, and one for differentiating between specific types of stigmatizing attitudes. Secondly, to identify the levels of suicide literacy, a content analysis was conducted on 4969 Weibo posts related to social media suicide. RESULTS: Firstly, the model accuracy ranged from 66.15% to 72.79%. Secondly, a total of 11.67% of the Weibo posts (n = 580) contained misinformation about suicide. In the category of knowledge of signs, 27.93% and 18.10% of posts endorsed the stigmatizing views that "suicide happens without warning" and "people who want to attempt suicide cannot change their mind quickly," both of which were related to a stigmatizing belief that a suicide attempt on social media is not genuine. In the category of knowledge of treatments, 35.17% of posts endorsed the stigmatizing view that "people who have thoughts about suicide should not tell others about it." DISCUSSION: This paper presents an opportunity for the dissemination of targeted online campaigns to increase mental health literacy and help-seeking.
INTRODUCTION: Broadcasting a suicide attempt on social media has become a public concern in China. Stigmatizing attitudes around such broadcast can limit help-seeking and increase the likelihood of death. To reduce stigmatizing attitudes, this paper aims to detect stigma expressions in social media posts through language use patterns and then identify suicide literacy in responses to such broadcast. METHODS: Firstly, to examine linguistic patterns of stigma expressions, 6632 Weibo posts with keywords were collected and analyzed. Using 102 linguistic features, 2 classification models were built: one for differentiating between stigmatizing and nonstigmatizing attitudes, and one for differentiating between specific types of stigmatizing attitudes. Secondly, to identify the levels of suicide literacy, a content analysis was conducted on 4969 Weibo posts related to social media suicide. RESULTS: Firstly, the model accuracy ranged from 66.15% to 72.79%. Secondly, a total of 11.67% of the Weibo posts (n = 580) contained misinformation about suicide. In the category of knowledge of signs, 27.93% and 18.10% of posts endorsed the stigmatizing views that "suicide happens without warning" and "people who want to attempt suicide cannot change their mind quickly," both of which were related to a stigmatizing belief that a suicide attempt on social media is not genuine. In the category of knowledge of treatments, 35.17% of posts endorsed the stigmatizing view that "people who have thoughts about suicide should not tell others about it." DISCUSSION: This paper presents an opportunity for the dissemination of targeted online campaigns to increase mental health literacy and help-seeking.