Predicting Multiple Risky Behaviors via Multimedia Content

Identifying signals associated with psychiatric illness utilizing language and images posted to Facebook

“…Most have utilized a computational approach to flag publicly available social media data from profiles of users who self-disclose having a diagnosis [27][28][29][30] without the ability to assess whether the individual meets diagnostic criteria for a psychiatric disorder. Other studies have extracted user data from anonymous individuals affiliated with an online mental health support group [31][32][33] , or have relied on clinicians to attempt to appraise the validity of a self-reported diagnoses 18,34,35 . Studies that link social media activity to clinically confirmed psychiatric symptoms or diagnoses are rare 11,18 , and without confirmed diagnoses, the clinical utility of findings is limited 36 .…”

Cue-Reactivity Among Young Adults With Problematic Instagram Use in Response to Instagram-Themed Risky Behavior Cues: A Pilot fMRI Study

“…Particularly in Asian cultures, binge drinking alcohol, publicly smoking cigarettes, online sexual content, and pornography are considered taboo. Thus, the inherent conservativeness of the Asian culture may explain why certain types of risky behaviors such as taking selfies from heights and dangerous locations, texting while driving and risqué interpersonal situations can be prevalently seen in their Instagram posts (Zhou et al, 2017). Furthermore, it is a known fact that impulsive people use smartphones as a gratifying means to engage in activities with no forethought about the consequences of their actions (Mitchell and Potenza, 2014).…”

“…Data mining of publicly available Instagram uploads has revealed a trend toward receiving likes for images known as negative emotional valence type of pictures. Selfies related to illicit drugs use and alcoholism, as well as selfies taken from heights and dangerous places, selfies taken while driving, and selfies taken while performing dangerous stunts; have been increasingly uploaded by users particularly in the young adult age group (Kurniawan et al, 2017;Zhou et al, 2017;Sherman et al, 2018b). Hence, Instagram addiction, concerning the attempts to get more online likes, has been attributed to the desire to gratify the need for peer acceptance and their perceived reward of gaining social popularity (Kircaburun and Griffiths, 2018).…”

Who is the "Human" in Human-Centered Machine Learning

“…Finally, after a full paper screen, we identified 11 new papers for analysis. Who is the "Human" in Human-Centered Machine Learning 147:31 [156] Degree of depression Instagram Chancellor et al 2016 [37] Mental illness severity Reece and Danforth 2017 [140] Depression Zhou, Zhan, and Luo 2017 [186] Depression; eating disorders Sina Weibo Cheng et al 2017 [41] 5 risk factors for suicidality -suicide probability; Weibo suicide communication; depression; anxiety; stress levels Guan et al 2015 [81] High suicide risk Huang et al 2015 [93] Suicidal ideation Huang et al 2014 [94] Suicidal ideation Lin et al 2014 [115] Stressed Lin et al 2016 [116] Stressed; stress item (What is causing stress) Wang et al 2013 [177] Depression Zhang et al 2015 [184] Suicide risk score (SPS value) Zhao, Jia, and Feng 2015 [185] Stress Reddit De Choudhury et al 2016' [55] Suicidal ideation Gkotsis et al 2017 [77] Bipolar disorder; borderline personality disorder; schizophrenia; anxiety; depression; self harm; suicide crisis Saha and De Choudhury 2017 [148] High or low stress Shen and Rudzicz 2017 [160] Anxiety Tumblr Chancellor, Mitra, and De Choudhury 2016 [38] Recovery from anorexia De Choudhury 2015 [50] Anorexia content; Anorexia versus in-recovery Simms et al 2017 [164] Cognitive distortions Twitter Benton, Mitchell, and Hovy 2017 [19] Non-neurotypical; anxiety; depression; suicide; eating disorder; panic attack; schizophrenia; bipolar disorder; post-traumatic stress disorder Birnbaum et al 2017 [23] Schizophrenia Braithwaite et al 2016 [28] Suicidal communication Burnap, Colombo, and Scourfield 2015 [31] Suidical vs 5 other classes about suicide-related communication Coppersmith, Dredze, and Harman 2014 [45] Bipolar disorder; depression; post-traumatic stress disorder; seasonal affective disorder Coppersmith et al 2015 [46] Anxiety; bipolar disorder; borderline personality disorder; depression; eating disorder; obssesive compulsive disorder; post-traumatic stress disorder; schizophrenia; seasonal affective disorder Coppersmith, Harman, and Dredze 2014 [47] Post-traumatic stre...…”