The Data

The most trusted content sensitivity dataset on the internet.

Since 2011, our community has tracked content that matters for people in crisis. Every rating, comment, and timestamp below was contributed by people who wanted to help others watch safely.

Community Ratings

Crowdsourced yes/no answers, comments, and timestamps. Freely available on DoesTheDogDie.com for everyone, always.

20,083,151

Yes / No ratings submitted by the community

925,632

Comments adding context and detail

7,176

Community-submitted timestamps

Titles covered75,738

Movies47,875

TV Shows12,970

Books8,095

Video Games4,179

Scene Alerts

Our most detailed data. Each Scene Alert is professionally produced by paid contributors and funded by subscribers.

Four data points for each Scene Alert:

Warning before the scene starts
A description of what happens immediately before the trigger — so you know it's coming with time to prepare or step away.
Trigger timestamp
The exact timestamp the triggering content begins.
Trigger description
A spoiler-conscious description of what happens at the trigger moment, written to inform without upsetting. Delivered as an AI-normalized summary for consistent formatting across the dataset. The raw contributor descriptions are available as a paid add-on.
Skip-to timestamp
An exact point to jump to — past the trigger, back into the film safely.

23,071

Scene Alerts

188

Movies

205

TV Episodes (26 shows)

Ratings by Category

How our coverage breaks down across the trigger categories.

Category	Ratings	Comments	Community Timestamps	Scene Alerts
▶ Violence	2,526,921	129,405	580	4,497
▶ Violence	612,946	38,893	195	1,969
blood or gore	193,330	17,211	86	1,374
drownings	135,542	7,658	13	53
nuclear explosions	132,443	3,554	5	13
gun violence	150,578	10,371	80	511
fires	1,050	96	8	18
	3	3	3	0
▶ Vehicular	480,828	18,950	95	538
car crashes	142,767	7,394	29	135
planes crashing	134,519	3,470	15	44
people getting hit by cars	133,162	6,009	13	88
car honk / tire screech	69,434	2,055	38	269
people hit by trains	946	22	0	2
▶ Abuse	961,280	50,928	151	1,070
child abuse	182,454	13,849	49	275
domestic violence	165,127	8,940	18	193
gaslighting	150,393	6,902	22	68
stalking	152,247	8,624	6	97
abused becomes abuser	64,976	2,461	1	32
abusive parents	70,597	4,532	18	171
abused forgives abuser	55,772	2,244	2	17
abuse with belt	50,172	730	2	10
women brutalized for spectacle	62,495	2,301	23	165
corporal punishment	1,313	53	2	6
emotional or verbal abuse	1,285	96	2	28
elder abuse	1,016	37	0	0
teachers abusing students	1,228	57	0	5
abuser's point of view	1,295	47	0	0
the phrase "good boy" or "good girl"	910	55	6	3
▶ Assault	375,121	18,719	128	895
restraints	94,988	6,554	45	437
druggings	67,335	3,533	13	138
held under water	61,791	2,323	13	43
beaten up by bully	54,901	2,354	5	100
women slapped	50,862	2,258	21	45
mouth covering	43,305	1,577	21	130
robberies or muggings	935	50	5	1
home invasions	1,002	68	3	1
	2	2	2	0
▶ Natural Disasters	15,058	200	1	7
tsunamis	15,058	200	1	7
▶ Large-scale Violence	81,688	1,715	10	18
9/11	75,421	1,338	2	3
mass casualties	1,641	156	5	1
apocalypse or end of the world	1,269	51	0	0
genocide	1,147	43	2	4
building collapses	933	48	1	2
war	1,277	79	0	8
▶ Sexual Content/Assault	1,271,624	71,477	501	1,821
▶ Sex	736,906	36,828	124	1,080
sexual content	177,821	13,752	40	345
incest	146,683	5,353	11	49
sexual objectification	77,343	3,913	13	145
nude scenes	82,603	6,174	36	320
sexualized minor	87,923	3,987	11	106
bestiality	69,289	1,179	8	34
lose virginity	50,083	1,307	0	32
BDSM	43,987	1,113	4	47
masturbation	1,174	50	1	2
▶ Sexual Assault	534,718	34,649	377	741
sexual assault	204,516	21,010	233	330
onscreen sexual assaulted	105,918	4,721	80	113
sexual assault on men is a joke	62,009	1,210	3	39
pedophilia	84,679	4,236	17	95
sexual assault mentions	73,735	3,317	37	161
human trafficking	1,146	33	1	1
dubious consent or sexual coercion	1,362	93	3	1
rape victims not believed	1,350	26	0	1
	1	1	1	0
	2	2	2	0
▶ Death, Grief & Loss	1,079,398	60,117	224	1,918
▶ Family	632,904	37,021	40	670
parents dying	173,675	13,353	13	222
cheating	144,297	7,850	4	137
kidnapping	141,813	8,143	8	113
dear toy destruction	109,812	3,383	4	12
family dies	61,099	4,120	9	167
family arguments	1,232	91	0	18
accidental killing of a loved one	976	81	2	1
▶ Death	274,708	13,976	165	1,117
self-sacrifice	66,064	3,272	12	52
non-human death	64,026	2,464	36	106
someone dies	76,928	4,352	71	639
major character dies	63,784	3,555	24	290
corpses	1,438	151	14	22
elderly people dying	1,244	76	1	2
funeral or cemetery scenes	1,223	105	6	6
	1	1	1	0
▶ Abandonment	126,606	7,640	14	116
child abandonment	77,388	5,618	8	53
leave without goodbye	49,218	2,022	6	63
▶ Loss	45,180	1,480	5	15
artifact destroyed	44,288	1,408	4	14
job loss	892	72	1	1
▶ Children & Babies	1,031,372	35,427	93	394
▶ Pregnancy	686,858	15,982	38	172
miscarriages	135,232	2,371	6	15
childbirth	134,249	3,925	15	20
abortions	129,801	2,395	0	11
pregnant people deaths	128,250	2,329	2	18
stillbirths	78,235	936	3	6
babies/unborn	81,091	4,026	12	102
▶ Children	344,514	19,445	55	222
kids dying	183,163	14,879	30	137
crying babies	89,391	2,802	21	76
infant abduction	69,755	1,634	1	9
adoption or foster care themes	1,198	87	0	0
children getting lost	1,007	43	3	0
▶ Animals	2,627,854	117,452	2,377	2,198
▶ Animal Distress	641,004	21,772	369	713
animal abuse	198,561	12,245	238	297
animal fighting	169,472	1,753	5	32
animals harmed during making	77,263	1,855	15	44
harmed rabbits	65,431	1,416	23	37
abandoned animals	63,713	1,773	14	53
sad animals	63,389	2,512	65	236
animal attacks	1,607	165	5	10
animals hit by vehicles	1,568	53	4	4
▶ Animal Death	1,377,886	74,655	1,732	1,086
dogs dying	282,455	18,940	360	92
horses dying	181,550	3,399	43	52
cats dying	198,807	6,370	106	40
animals (besides dog/cat/horse) dying	254,640	26,901	779	458
dragons dying	173,304	2,216	5	30
dead animals	181,291	13,021	321	312
pets die	105,839	3,808	118	102
▶ Animal Phobia	608,964	21,025	276	399
spiders	165,704	5,224	101	69
bugs	169,288	9,425	102	214
snakes	158,642	4,463	58	52
alligators or crocodiles	57,372	861	3	35
sharks	56,638	949	7	29
rats or mice	1,320	103	5	0
▶ Mental Health	2,411,215	118,656	340	2,143
▶ Addiction	496,763	29,176	43	382
drug use	173,584	12,378	25	201
alcohol abuse	165,063	9,449	13	92
addiction	154,913	7,210	2	67
addiction stigma	971	23	1	2
bad psychedelic trips	1,020	28	1	4
smoking or vaping	1,212	88	1	16
▶ Mental Health	1,145,269	41,297	79	971
body dysmorphia	127,130	3,208	0	15
eating disorders	137,835	4,152	2	15
anxiety attacks	129,257	5,728	5	155
autism abuse	122,392	2,108	0	10
misophonia	77,241	4,678	35	295
violent mentally ill person	94,469	4,805	1	23
PTSD	80,246	4,754	4	61
D.I.D. misrepresentation	54,116	907	0	8
body dysphoria	49,050	747	0	3
ABA therapy	43,901	152	0	3
reality unhinged	49,738	3,024	2	134
mental illness	47,144	2,956	3	45
meltdowns	43,687	1,661	7	99
autism misrepresented	48,348	739	0	2
dissociation, depersonalization, or derealization	34,203	1,363	1	91
agoraphobia	886	13	0	0
amnesia or memory loss	993	81	4	1
brainwashing or mind control	1,021	74	7	6
people not being believed	965	91	5	1
mental illness stigma	892	38	2	4
hypochondria accusations	831	1	0	0
personality disorders demonized	924	17	1	0
▶ Paranoia	129,108	7,369	17	243
fourth wall	77,220	4,076	5	53
being watched	51,888	3,293	12	190
▶ Drugs/Alcohol	72,234	1,678	4	25
overdose	72,234	1,678	4	25
▶ Relationships	74,283	4,453	16	58
large age gap	72,321	4,280	5	45
betrayal	986	78	11	10
breakups or divorce	976	95	0	3
▶ Self Harm	493,558	34,683	181	464
people dying by suicide	175,173	18,096	97	202
self harming	150,326	7,208	42	141
"I'll kill myself"	88,304	4,081	14	39
suicide attempts	79,755	5,298	28	82
▶ Discrimination	2,366,098	85,249	175	1,021
▶ Social	218,007	5,760	5	54
homelessness	69,295	3,675	2	24
fat suits	54,497	493	0	6
anti-abortion	50,934	618	0	5
existentialism	41,242	904	1	18
climate change	1,047	26	0	1
environmental destruction	992	44	2	0
▶ LGBTQ+	279,950	4,916	13	48
bisexual cheating	60,612	990	1	15
deadnaming / birthnaming	55,425	1,008	2	1
transphobic slurs	59,281	944	6	11
trans person depicted predatorily	55,411	861	1	10
LGBT+ person outed	45,199	1,030	3	11
biphobia or bi erasure	1,107	21	0	0
conversion therapy	1,621	20	0	0
queerbaiting	1,294	42	0	0
▶ Race	488,697	14,005	26	132
black guy dies first	137,344	4,569	2	12
antisemitism	116,748	3,164	2	14
n-word usage	121,670	2,186	0	53
minority misrepresentation	53,376	3,051	10	40
blackface	53,923	750	5	7
Islamophobia	1,164	26	0	1
Nazis or swastikas	1,355	98	0	1
anti-Indigenous racism	1,113	69	5	4
slavery	1,081	57	2	0
cultural appropriation	923	35	0	0
▶ Disability	131,690	3,387	13	51
R-slur	82,647	1,602	9	28
disabled played by able-bodied	44,839	1,633	1	19
disabled people dying	951	41	2	0
disability demonized	1,086	41	0	3
faked disabilities	1,086	31	1	1
miracle cures	1,081	39	0	0
▶ Religious	89,650	6,221	18	190
religion discussed	45,192	4,120	13	145
demons or Hell	41,475	2,000	1	36
religious abuse	957	23	1	8
cults	1,095	47	1	0
religious mockery or persecution	931	31	2	1
▶ Law Enforcement	147,920	8,145	19	138
copaganda	98,818	4,951	7	23
incarceration	46,993	3,073	7	113
police brutality	1,041	49	4	1
executions	1,068	72	1	1
▶ Sexism	68,880	2,141	13	8
male crying ridicule	66,781	2,028	8	8
women portrayed as incompetent	1,147	62	3	0
gender essentialism	952	51	2	0
▶ Prejudice	941,304	40,674	68	400
LGBT people dying	148,124	5,941	1	23
hate speech	137,421	8,760	14	120
misgendering	137,527	4,365	4	19
fat jokes	131,047	5,095	11	56
ableism	119,829	8,022	19	111
homophobic slurs	124,674	4,758	9	45
man in a dress jokes	92,852	3,061	8	20
aphobia	47,878	612	0	5
"emo" jokes	1,075	20	1	1
prejudice against children or teens	877	40	1	0
▶ Medical & Health	1,005,592	33,094	109	589
▶ Medical	780,997	26,976	101	507
needles or syringes are used	147,381	6,720	56	161
hospital scenes	155,004	8,710	21	225
cancer	142,128	4,094	6	44
electro-therapy	135,099	2,379	4	9
mental institutions	140,014	3,589	2	39
menstruation	43,610	907	1	20
heart attack	14,825	426	5	7
involuntary medical treatment	936	50	2	1
CPR	976	20	1	0
surgery or medical procedures	1,024	81	3	1
▶ Sickness	224,595	6,118	8	82
strokes	59,984	643	1	10
chronic illnesses	56,488	2,168	2	21
dementia/Alzheimer's	58,453	1,413	0	10
terminal illness	45,744	1,785	3	41
diabetes mocked or misrepresented	989	8	1	0
COVID-19	2,029	71	1	0
allergic reactions	908	30	0	0
▶ Phobias & Sensory	2,702,634	134,863	2,196	5,113
▶ Gross	737,761	52,285	1,747	933
spitting	134,241	6,424	52	201
vomiting	235,101	33,465	1,630	250
audio gore	116,711	3,434	22	279
wet/soiled pants	94,316	3,683	13	45
someone is eaten	56,756	2,620	10	69
farting	49,373	975	4	37
defecation	51,262	1,683	15	52
	1	1	1	0
▶ Noxious	475,430	23,818	247	2,776
flashing lights or images	136,701	8,613	103	849
shaky cam	126,099	4,770	16	249
obscene language/gestures	63,150	3,954	9	315
sudden loud noises	48,022	1,961	41	579
underwater scenes	42,716	1,958	8	74
screaming	54,470	2,346	44	676
secondhand embarrassment	860	36	3	1
sirens or alarms	854	41	8	12
high-pitched noises	836	39	4	7
repetitive sounds	788	50	4	10
glitches or technology errors	932	48	5	4
	2	2	2	0
▶ Fear	1,086,903	43,473	187	1,210
jump scares	158,325	5,856	91	422
clowns	149,261	3,421	18	17
shower scenes	142,636	6,642	12	72
claustrophobic scenes	124,707	7,600	14	189
ghosts	151,161	6,094	8	105
demonic possession	145,034	4,978	4	67
mannequins	55,243	1,878	5	67
razors	53,285	1,608	8	18
trypophobia	44,332	1,152	4	20
bodies of water	55,792	3,793	6	230
dolls or puppets	1,360	123	5	0
zombies	1,326	60	4	0
countdowns or time pressure	1,015	108	3	2
extreme heights	968	76	4	1
backwards speech	983	19	1	0
aliens	1,475	65	0	0
▶ Spoiler	322,069	13,920	6	146
Santa (et al) spoilers	128,666	1,392	1	2
sad endings	148,204	10,918	2	63
end credit scenes	44,164	1,543	3	80
cliffhanger endings	1,035	67	0	1
▶ Creepy Crawly	50,011	410	8	25
bedbugs	47,507	287	1	23
bugs being killed	1,344	90	3	2
cockroaches	1,159	32	3	0
	1	1	1	0
▶ Live Theatre	30,460	957	1	23
audience participation	9,242	198	0	0
smoke or haze	8,067	525	0	13
onstage flying	4,209	53	0	0
audience entrance	4,278	14	0	0
live gunfire	4,664	167	1	10
▶ Bodily Harm	3,090,212	139,599	577	3,377
▶ Appendages	689,359	28,062	113	602
finger or toe mutilation	146,371	5,832	29	90
bones breaking	142,841	6,851	26	133
amputation	131,090	6,818	17	126
genital trauma/mutilation	112,697	3,990	17	63
Achilles Tendon injury	67,712	616	3	9
hand damage	46,724	3,127	17	151
dislocations	40,897	810	2	30
stepping on nails	1,027	18	2	0
▶ Head	503,898	21,269	91	362
eye mutilation	155,875	8,060	32	129
teeth damage	142,374	4,083	15	73
heads getting squashed	147,956	6,265	17	57
decapitation	55,660	2,790	24	102
dentist scenes	1,081	18	2	0
facial distortion	952	53	1	1
▶ Neck	442,340	23,002	139	700
hangings	142,801	5,936	52	63
choking	137,018	10,412	31	274
asphyxiation	61,980	2,169	1	59
chokings	51,807	2,170	30	187
throat mutilation	48,734	2,315	25	117
▶ Whole Body	1,454,615	67,266	234	1,713
people being burned alive	157,950	9,239	35	78
shaving or cutting	148,079	8,020	25	155
torture	166,172	9,063	23	175
seizures	134,685	2,830	4	25
falling deaths	141,061	7,996	20	87
buried alive	129,933	3,156	5	33
cannibalism	131,075	4,514	2	42
excessive gore	104,884	5,821	8	283
falling down stairs	69,060	2,299	13	36
crushed to death	70,728	2,772	7	30
body horror	76,533	4,091	17	195
unconscious	66,687	3,917	18	272
stabbings	54,914	3,413	45	301
acid injuries	944	38	3	0
scars	956	62	1	0
self-surgery	946	27	0	1
	7	7	7	0
	1	1	1	0
▶ Other	4	4	4	0
▶ Other	4	4	4	0
	2	2	2	0
	2	2	2	0

Categories ordered by total community ratings. Scene Alert timestamps are professionally produced and expanding monthly.

Build with this data

Community ratings are cheap and predictable to build on. Scene Alerts and the premium data are optional add-ons.

Free

Commercial

$50/mo

Enterprise

Data access

Yes/no community ratings

✓

Community comments

✓

Community-submitted timestamps

✓

Scene Alerts (cue+trigger/skip timestamps)

—

✓

Raw contributor descriptions

—

✓

Bulk data exports

—

✓

ML training rights

—

✓

Usage

Commercial use

—

✓

Rate limit

30 req/min

600 req/min

Custom

Requests per month

5,000

500,000

Unlimited

Support

Support channel

Community

Dedicated

Attribution required

Yes

Negotiable

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API v3.0 Documentation →

API Terms of Service

The most trusted content sensitivity dataset on the internet.

Community Ratings

Scene Alerts

Warning before the scene starts

Trigger timestamp

Trigger description

Skip-to timestamp

Ratings by Category

Build with this data