Causal Effects of Trigger Words in Social Media Discussions: A Large-Scale Case Study about UK Politics on Reddit

Dimosthenis Antypas; Christian Arnold; Nedjma Ousidhoum; Carla Perez-Almendros; Jose Camacho-Collados

doi:10.1145/3795766.3799750

Causal Effects of Trigger Words in Social Media Discussions: A Large-Scale Case Study about UK Politics on Reddit

Dimosthenis Antypas
, Christian Arnold
, Nedjma Ousidhoum
, Carla Perez-Almendros
, Jose Camacho-Collados

International Development

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Political debates on social media often escalate quickly, leading to increased engagement as well as more emotional and polarised exchanges. Trigger points [43] represent moments when individuals feel that their understanding of what is fair, normal, or appropriate in society is being questioned. Analysing Reddit discussions, we examine how trigger points shape online debates and assess their impact on engagement and affect. Our analysis is based on over 100 million comments from subreddits centred on a predefined set of terms identified as trigger words in UK politics. We find that mentions of these terms are associated with higher engagement and increased animosity, including more controversial, negative, angry, and hateful responses. These results position trigger words as a useful concept for modelling and analysing online polarisation.

Original language	English
Title of host publication	Websci '26
Subtitle of host publication	Proceedings of the 18th ACM Web Science Conference 2026
Editors	Wolf-Tilo Balke, Florian Plötzky, Gianluca Demartini, Stefan Dietze, Jennifer Golbeck, Sierra Kaiser, Rezvaneh Rezapour
Publisher	Association for Computing Machinery (ACM)
Pages	359-369
Number of pages	11
ISBN (Print)	9798400725043
DOIs	https://doi.org/10.1145/3795766.3799750
Publication status	Published - 25 May 2026
Event	18th ACM Web Science Conference 2026 - Braunschweig, Germany Duration: 26 May 2026 → 29 Jun 2026

Conference

Conference	18th ACM Web Science Conference 2026
Abbreviated title	WebSci '26
Country/Territory	Germany
City	Braunschweig
Period	26/05/26 → 29/06/26

Keywords

Affective polarization
Causal effect
Computational social science
Hate speech
Reddit
Trigger words
UK politics

Access to Document

10.1145/3795766.3799750Licence: Creative Commons: Attribution-NonCommercial-NoDerivs (CC BY-NC-ND)

Cite this

Antypas, D., Arnold, C., Ousidhoum, N., Perez-Almendros, C., & Camacho-Collados, J. (2026). Causal Effects of Trigger Words in Social Media Discussions: A Large-Scale Case Study about UK Politics on Reddit. In W.-T. Balke, F. Plötzky, G. Demartini, S. Dietze, J. Golbeck, S. Kaiser, & R. Rezapour (Eds.), Websci '26: Proceedings of the 18th ACM Web Science Conference 2026 (pp. 359-369). Association for Computing Machinery (ACM). https://doi.org/10.1145/3795766.3799750

Antypas, Dimosthenis ; Arnold, Christian ; Ousidhoum, Nedjma et al. / Causal Effects of Trigger Words in Social Media Discussions : A Large-Scale Case Study about UK Politics on Reddit. Websci '26: Proceedings of the 18th ACM Web Science Conference 2026. editor / Wolf-Tilo Balke ; Florian Plötzky ; Gianluca Demartini ; Stefan Dietze ; Jennifer Golbeck ; Sierra Kaiser ; Rezvaneh Rezapour. Association for Computing Machinery (ACM), 2026. pp. 359-369

@inproceedings{1efe57114d2d4608a6885934b6108fdf,

title = "Causal Effects of Trigger Words in Social Media Discussions: A Large-Scale Case Study about UK Politics on Reddit",

abstract = "Political debates on social media often escalate quickly, leading to increased engagement as well as more emotional and polarised exchanges. Trigger points [43] represent moments when individuals feel that their understanding of what is fair, normal, or appropriate in society is being questioned. Analysing Reddit discussions, we examine how trigger points shape online debates and assess their impact on engagement and affect. Our analysis is based on over 100 million comments from subreddits centred on a predefined set of terms identified as trigger words in UK politics. We find that mentions of these terms are associated with higher engagement and increased animosity, including more controversial, negative, angry, and hateful responses. These results position trigger words as a useful concept for modelling and analysing online polarisation.",

keywords = "Affective polarization, Causal effect, Computational social science, Hate speech, Reddit, Trigger words, UK politics",

author = "Dimosthenis Antypas and Christian Arnold and Nedjma Ousidhoum and Carla Perez-Almendros and Jose Camacho-Collados",

year = "2026",

month = may,

day = "25",

doi = "10.1145/3795766.3799750",

language = "English",

isbn = "9798400725043",

pages = "359--369",

editor = "Wolf-Tilo Balke and Florian Pl{\"o}tzky and Gianluca Demartini and Stefan Dietze and Jennifer Golbeck and Sierra Kaiser and Rezvaneh Rezapour",

booktitle = "Websci '26",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

note = "18th ACM Web Science Conference 2026, WebSci '26 ; Conference date: 26-05-2026 Through 29-06-2026",

}

Antypas, D, Arnold, C, Ousidhoum, N, Perez-Almendros, C & Camacho-Collados, J 2026, Causal Effects of Trigger Words in Social Media Discussions: A Large-Scale Case Study about UK Politics on Reddit. in W-T Balke, F Plötzky, G Demartini, S Dietze, J Golbeck, S Kaiser & R Rezapour (eds), Websci '26: Proceedings of the 18th ACM Web Science Conference 2026. Association for Computing Machinery (ACM), pp. 359-369, 18th ACM Web Science Conference 2026, Braunschweig, Lower Saxony, Germany, 26/05/26. https://doi.org/10.1145/3795766.3799750

Causal Effects of Trigger Words in Social Media Discussions: A Large-Scale Case Study about UK Politics on Reddit. / Antypas, Dimosthenis; Arnold, Christian; Ousidhoum, Nedjma et al.
Websci '26: Proceedings of the 18th ACM Web Science Conference 2026. ed. / Wolf-Tilo Balke; Florian Plötzky; Gianluca Demartini; Stefan Dietze; Jennifer Golbeck; Sierra Kaiser; Rezvaneh Rezapour. Association for Computing Machinery (ACM), 2026. p. 359-369.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Causal Effects of Trigger Words in Social Media Discussions

T2 - 18th ACM Web Science Conference 2026

AU - Antypas, Dimosthenis

AU - Arnold, Christian

AU - Ousidhoum, Nedjma

AU - Perez-Almendros, Carla

AU - Camacho-Collados, Jose

PY - 2026/5/25

Y1 - 2026/5/25

N2 - Political debates on social media often escalate quickly, leading to increased engagement as well as more emotional and polarised exchanges. Trigger points [43] represent moments when individuals feel that their understanding of what is fair, normal, or appropriate in society is being questioned. Analysing Reddit discussions, we examine how trigger points shape online debates and assess their impact on engagement and affect. Our analysis is based on over 100 million comments from subreddits centred on a predefined set of terms identified as trigger words in UK politics. We find that mentions of these terms are associated with higher engagement and increased animosity, including more controversial, negative, angry, and hateful responses. These results position trigger words as a useful concept for modelling and analysing online polarisation.

AB - Political debates on social media often escalate quickly, leading to increased engagement as well as more emotional and polarised exchanges. Trigger points [43] represent moments when individuals feel that their understanding of what is fair, normal, or appropriate in society is being questioned. Analysing Reddit discussions, we examine how trigger points shape online debates and assess their impact on engagement and affect. Our analysis is based on over 100 million comments from subreddits centred on a predefined set of terms identified as trigger words in UK politics. We find that mentions of these terms are associated with higher engagement and increased animosity, including more controversial, negative, angry, and hateful responses. These results position trigger words as a useful concept for modelling and analysing online polarisation.

KW - Affective polarization

KW - Causal effect

KW - Computational social science

KW - Hate speech

KW - Reddit

KW - Trigger words

KW - UK politics

U2 - 10.1145/3795766.3799750

DO - 10.1145/3795766.3799750

M3 - Conference contribution

SN - 9798400725043

SP - 359

EP - 369

BT - Websci '26

A2 - Balke, Wolf-Tilo

A2 - Plötzky, Florian

A2 - Demartini, Gianluca

A2 - Dietze, Stefan

A2 - Golbeck, Jennifer

A2 - Kaiser, Sierra

A2 - Rezapour, Rezvaneh

PB - Association for Computing Machinery (ACM)

Y2 - 26 May 2026 through 29 June 2026

ER -

Antypas D, Arnold C, Ousidhoum N, Perez-Almendros C, Camacho-Collados J. Causal Effects of Trigger Words in Social Media Discussions: A Large-Scale Case Study about UK Politics on Reddit. In Balke WT, Plötzky F, Demartini G, Dietze S, Golbeck J, Kaiser S, Rezapour R, editors, Websci '26: Proceedings of the 18th ACM Web Science Conference 2026. Association for Computing Machinery (ACM). 2026. p. 359-369 doi: 10.1145/3795766.3799750

Causal Effects of Trigger Words in Social Media Discussions: A Large-Scale Case Study about UK Politics on Reddit

Abstract

Conference

Keywords

Access to Document

Fingerprint

Cite this