Mapping Multiclass-Targeted Hate Speech in Online Discourse: An Open Dataset

DATASET	OBJECTIVE	CLASSIFICATION SCHEMA	MAIN CATEGORY CLASSIFICATION	SUBCATEGORY CLASSIFICATION
Mody et al. (2023)	Hate speech detection	2-class (hate, non-hate)	No	No
Davidson et al. (2017)	Detect hate speech from offensive and normal language	3-class (hate, offensive, normal)	No	No
Mollas et al. (2022)	Multi-label hate speech detection	8-class (violence, directed vs general, gender, race, national origin, disability, religion, sexual orientation)	Yes	No
Waseem and Hovy (2016)	Identify racism and sexism on Twitter	3-classes (racism, sexism, neither)	Yes	No
Mathew et al. (2021)	Explainable hate speech classification with target identification	3-class (hate, offensive, normal)	No	No
Walsh and Greaney (2025)	Categorize hate speech across multiple groups	5-class (ethnicity, gender, sexuality, religion, non-hate)	Yes	No
Proposed data	Hate speech categorization	14-classes	Yes	Yes

Table 2

Label distribution in the dataset.

MAIN CATEGORY	SUBCATEGORY	COUNT
Gender-Based Hate Speech	Misogyny	2019
Gender-Based Hate Speech	Misandry	29
Immigration and Xenophobic Hate Speech	Anti-Immigrant Hate Speech	1882
	Anti-Refugee Hate Speech	379
	Xenophobia	51
Religious Hate Speech	Islamophobia	167
Religious Hate Speech	Anti-Christian Hate Speech	3
Racial and Ethnic Hate Speech	Anti-Black Hate Speech	105
	Anti-Hispanic Hate Speech	16
	Anti-Semitic Hate Speech	4
	Anti-Asian Hate Speech	2
Profanity and General Abuse	–	674
Threats and Violence	–	106
Hate Speech toward Countries	–	18

Data curation and re-annotation workflow.

Table 3

Masked lexical indicators used for the dataset selection process.

WORDS	HATE SPEECH CONTEXT TYPE
F* (profanity), sh* (profanity), d* (insult), j* (insult), b* (insult), a* (insult), idiot, moron, stupid, trash, garbage, scum, vermin, animal, savage	Profanities and general insults
B* (gender-slur), h* (gender-slur), s* (gender-slur), w* (gender-slur), p*** (gender-slur), gold-digger, feminazi	Gender-based slurs and sexist language
N* (racial slur), n* (racial slur), k*** (racial slur), Pakistani, black, white, Arab, Mexican, Asian, African, monkey	Race-related or ethnicity-targeted words
Muslim, jew, Islamic, Christian, hindu, jihad, jihadist, infidel, terrorist	Religion-related expressions
Immigrant, refugee, migrant, alien, asylum seeker, #sendthemback, invader, invasion, illegals, #buildthatwall, foreigner	Anti-immigrant and anti-refugee language
Chinese, China, Russian, Russia, middle eastern, Australia, American	Country or nationality targeting terms

Table 4

Misclassified hate speech instances in the dataset.

REMOVED HATE SPEECH SAMPLES
Well that’s just great! @user @user
@user Simply put
@user @user @user @user @user @user @user @user @user @user @user @user @user @user @user @user @user @user @user

Table 5

Examples from the dataset.

TEXT	LABEL
No matter what color a girl is she still a [slur: derogatory term for women]	Gender-Based Hate Speech (Misogyny)
@user @user thiers none because not all men rape	Gender-Based Hate Speech (Misandry)
Illegal Alien Hit Man, Dragged Him For Blocks In Deadly DUI Crash #BuildTheWall #NoAmnesty #NoDACA #DeportThemAll #KeepAmericaSafe	Immigration and Xenophobic Hate Speech (Anti-Immigrant Hate Speech)
@user @user real talk do you have eyes or were they gouged out by a [hate slur: derogatory anti-refugee term]?	Immigration and Xenophobic Hate Speech (Anti-Refugee Hate Speech)
to hell with the #Tories. #SendThemHome	Immigration and Xenophobic Hate Speech (Xenophobia)
Victory for Trump ! But only 6 islamic countries now are stopped for immigration into USA ! There are 34 islamic countries more. To beware the USA from terrorists these also has to get banned.	Religious Hate Speech (Islamophobia)
God is dead, Jesus is a [profanity] and the Virgin Mary was a [slur: derogatory term for women].	Religious Hate Speech (Anti-Christian Hate Speech)
#sendthemback if your children want a peacefull life, without [sexual violence reference] on every corner.#forza. #Italia ##NoMoreAfricans !!	Racial and Ethnic Hate Speech (Anti-Black Hate Speech)
Mexico’s not sending their best. They’re dumping their killers aka garbage on us. #StopTheInvasion #DeportThemAll #NoAmnesty #BuildTheWall	Racial and Ethnic Hate Speech (Anti-Hispanic Hate Speech)
Let’s me honest, Jews offer things and the white women are just [slur: sexualized derogatory term]. Muslims [sexual violence reference] rape and beat white women.	Racial and Ethnic Hate Speech (Anti-Semitic Hate Speech)
@user <– another son of a dirty [profanity] Korean [ethnic slur] [slur]	Racial and Ethnic Hate Speech (Anti-Asian Hate Speech)
Your [slur: derogatory insult] ass disgusts me so much	Profanity and General Abuse
@user @user lol. you selfish terrorist [profanity] should be boiled alive. Maybe lynched by neonazis. Would serve you right.	Threats and Violence
@user Bloody Germany who needs Germany we dont want their Visa plans were are fed up of being over ran by migrants no Uk Jobs threaten	Hate Speech toward Countries

Table 6

Lexical statistics per class.

LABEL	TOTAL WORDS	MAXIMUM TEXT LENGTH	TOTAL UNIQUE WORDS
Gender-Based Hate Speech (Misogyny)	37,184	57	5,964
Gender-Based Hate Speech (Misandry)	594	93	309
Immigration and Xenophobic Hate Speech (Anti-Immigrant Hate Speech)	57,357	88	8,905
Immigration and Xenophobic Hate Speech (Anti-Refugee Hate Speech)	10,362	59	2,906
Immigration and Xenophobic Hate Speech (Xenophobia)	1,350	54	634
Religious Hate Speech (Islamophobia)	4,898	69	1,678
Religious Hate Speech (Anti-Christian Hate Speech)	78	38	64
Racial and Ethnic Hate Speech (Anti-Black Hate Speech)	2,677	54	1,050
Racial and Ethnic Hate Speech (Anti-Hispanic Hate Speech)	441	50	260
Racial and Ethnic Hate Speech (Anti-Semitic Hate Speech)	88	34	73
Racial and Ethnic Hate Speech (Anti-Asian Hate Speech)	42	32	40
Profanity and General Abuse	12,767	70	3,181
Threats and Violence	2,419	64	995
Hate Speech toward Countries	664	62	396