The Number and Characteristics of Newspaper and Twitter Reports on Suicides and Road Traffic Deaths in Young People

Figures & data

TABLE 1. Characteristics of Stories in Twitter and Newspapers (Suicides and RTAs)

	Twitter		Newspapers
	Suicides: n (%)	RTAs: n (%)	Suicides: n (%)	RTAs: n (%)
N of 48-hour story peaks	93	66	112	76
Age of deceased—<16	41 (44.1%)	18 (27.3%)	50 (44.6%)	18 (23.7%)
−16+	52 (55.9%)	48 (72.7%)	62 (55.4%)	58 (76.3%)
Gender—Male	52 (55.9%)	37 (56.1)	56 (50.0%)	41 (54.0%)
—Female	41 (44.1%)	29 (43.9%)	56 (50.0%)	35 (46.1%)
Death within the study period	25 (26.9%)	29 (43.9%)	38 (33.9%)	34 (44.7%)
Case resulted in an open verdict	13 (14.0%)	N/A	28 (25.0%)	N/A
Bullying ever been reported	25 (26.9%)	N/A	31 (27.7%)	N/A
Social media connection ever been reported	24 (25.8%)	N/A	25 (22.3%)	N/A
Link ever been made to another case	30 (32.3%)	8 (12.1%)	26 (23.2%)	9 (11.8%)
Any related campaign or petition	18 (19.6%)	12 (18.2%)	29 (26.1%)	11 (14.5%)
Deceased has a criminal history	6 (6.5%)	N/A	9 (8.0%)	N/A
A related conviction	11 (11.8%)	24 (36.4%)	11 (9.8%)	28 (36.8%)
Memorial event or fundraising	12 (12.9%)	15 (22.7%)	15 (13.4%)	16 (21.1%)
Related research study or documentary	9 (9.7%)	N/A	10 (8.9%)	N/A

TABLE 2. Multi-Variate Negative Binomial Regression Models: Count of Suicide-Related Tweets and Newspaper Reports Within 48-hours of a Peak

Feature of story	Tweets (n = 93)			News reports (n = 112)
	IRR	coeff.	z	IRR	coeff.	z
Deceased is aged >16	1.04	0.04	0.09	1.17	0.16	0.77
Deceased is male	0.32	–1.14	–2.82	1.16	0.15	0.79
Death within study period	2.26	0.81	1.84	1.01	0.01	0.06
Bullying	4.43	1.49	2.82	1.80	0.59	2.46
Social media dimension	1.10	0.10	0.19	1.64	0.49	2.13
Link with case	1.04	0.04	0.10	1.79	0.58	2.56
Campaigning	9.70	2.27	3.32	1.35	0.30	1.19
Criminal history	1.29	0.25	0.24	0.69	–0.37	–0.90
Related conviction	3.12	1.14	1.91	1.88	0.63	1.92
Memorial/fundraising	0.69	–0.37	–0.63	1.02	0.02	0.07
Research/documentary	0.21	–1.55	–1.94	0.77	–0.26	–0.67
Log likelihood	–399.00			–289.07
Chi-square	46.48			24.75
p-value	p < .001			p = .01
McFadden’s R^2	0.06			0.04
LR test of alpha = 0	p < .001			p < .001

TABLE 3. Multi-Variate Negative Binomial Regression Models: Count of RTA Death-Related Tweets and Newspaper Reports Within 48-hours of a Peak

Feature of story	Tweets (n = 66)			News reports (n = 76)
	IRR	coeff.	z	IRR	coeff.	z
Deceased is aged >16	0.40	–0.91	–2.69	0.84	–0.17	–0.79
Deceased is male	0.43	–0.71	–2.54	0.59	–0.53	–2.63
Death within study period	2.83	1.04	3.07	1.89	0.64	2.71
Link with case	0.77	–0.26	–0.54	2.88	1.06	3.56
Campaigning	1.18	0.16	0.42	0.80	–0.23	–0.84
Related conviction	0.99	–0.01	0.04	1.18	0.16	0.72
Memorial/fundraising	1.79	0.58	1.64	1.43	0.36	1.55
Log likelihood	–265.87			–195.45
Chi-square	51.65			29.10
p-value	p < .001			p < .001
McFadden’s R^2	0.06			0.03
LR test of alpha = 0	p < .001			p < .001

TABLE 4. Comparison of Reports Per Case in Twitter and Newspapers: Suicides and Road Traffic Accidents (RTAs)

		Twitter reports				Newspaper reports
	n of cases	Mean (SD)	Median	IQR	ES*	Mean (SD)	Median	IQR	ES*
Suicides	81	125.98 (334.44)	15	2–60	0.27	12.00 (15.56)	5	2–16	0.07
RTAs	68	54.09 (148.66)	14	3–45		10.88 (15.97)	7	3–11

* Hedges’s g.