Prevalence, Substance and Responses to Hate Speech Against LGBTQ Communities on TikTok

Despite ongoing efforts, online hate speech remains a pervasive issue on social media, particularly affecting vulnerable groups such as LGBTQ communities. While there is extensive debate around how best to address this problem, counter speech is emerging as a promising solution. However, existing research has primarily focused on detecting hateful content, often overlooking broader aspects such as the specific topics of discrimination and the spread of countermeasures online. This study examines the prevalence of hate speech and counter speech in LGBTQ online spaces on TikTok, analysing day-to-day interactions to identify recurring themes and targets. Results reveal that hate speech is widespread: at least 3.5% of messages contain hateful content, spread by approximately 4% of users, and one in three videos attracts hate comments or replies, primarily targeting LGBTQ topics explicitly. Gender identity emerges as a major focus, with transgender and non-binary individuals being frequent targets. Although much hate engagement goes unanswered, when responses occur, they are often in the form of counter speech, especially when LGBTQ-related topics are targeted. These findings improve our understanding of the nature and extent of online hate speech against LGBTQ communities, confirm counter speech as an employed response, and provide a foundation for further research aimed at developing strategies to promote safer, more inclusive social media environments.

Authors

Institutions

Publication Details

Journal
Proceedings of the International AAAI Conference on Web and Social Media
Published
2025-06-07
DOI
https://doi.org/10.1609/icwsm.v19i1.35824
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prevalence, Substance and Responses to Hate Speech Against LGBTQ Communities on TikTok

Jürgen Pfeffer, Elena Pavan, Angelina Voggenreiter, Jordi Guillem Condom Tibau
Proceedings of the International AAAI Conference on Web and Social Media
Hate Speech and Cyberbullying Detection
article

Prevalence, Substance and Responses to Hate Speech Against LGBTQ Communities on TikTok

Jürgen Pfeffer, Elena Pavan, Angelina Voggenreiter, Jordi Guillem Condom Tibau
article en

Abstract

Despite ongoing efforts, online hate speech remains a pervasive issue on social media, particularly affecting vulnerable groups such as LGBTQ communities. While there is extensive debate around how best to address this problem, counter speech is emerging as a promising solution. However, existing research has primarily focused on detecting hateful content, often overlooking broader aspects such as the specific topics of discrimination and the spread of countermeasures online. This study examines the prevalence of hate speech and counter speech in LGBTQ online spaces on TikTok, analysing day-to-day interactions to identify recurring themes and targets. Results reveal that hate speech is widespread: at least 3.5% of messages contain hateful content, spread by approximately 4% of users, and one in three videos attracts hate comments or replies, primarily targeting LGBTQ topics explicitly. Gender identity emerges as a major focus, with transgender and non-binary individuals being frequent targets. Although much hate engagement goes unanswered, when responses occur, they are often in the form of counter speech, especially when LGBTQ-related topics are targeted. These findings improve our understanding of the nature and extent of online hate speech against LGBTQ communities, confirm counter speech as an employed response, and provide a foundation for further research aimed at developing strategies to promote safer, more inclusive social media environments.

Proceedings of the International AAAI Conference on Web and Social MediaVol. 19
University of Trento (IT), Technical University of Munich (DE)
Openalex Percentile: Top 94%
Hate Speech and Cyberbullying Detection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.