# Discursive objection strategies in online comments: Developing a classification schema and validating its training

arXiv: https://arxiv.org/abs/2405.08142 · HTML: https://mlsanity.com/paper/2405.08142/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 17 references that are in the map.
- First posted on arXiv 13 May 2024.

## Builds on (most cited first, 2 of 2)

- [Divergent discourse between protests and counter-protests: #BlackLivesMatter and #AllLivesMatter](https://mlsanity.com/paper/1606.06820/) (2016)
- [Still out there: Modeling and Identifying Russian Troll Accounts on Twitter](https://mlsanity.com/paper/1901.11162/) (2019)

## Built on by (most cited first, 1 of 1)

- [A Comparison of Human and ChatGPT Classification Performance on Complex Social Media Data](https://mlsanity.com/paper/2512.00673/) (2025)

## Abstract (arXiv)

Most Americans agree that misinformation, hate speech and harassment are harmful and inadequately curbed on social media through current moderation practices. In this paper, we aim to understand the discursive strategies employed by people in response to harmful speech in news comments. We conducted a content analysis of more than 6500 comment replies to trending news videos on YouTube and Twitter and identified seven distinct discursive objection strategies (Study 1). We examined the frequency of each strategy's occurrence from the 6500 comment replies, as well as from a second sample of 2004 replies (Study 2). Together, these studies show that people deploy a diversity of discursive strategies when objecting to speech, and reputational attacks are the most common. The resulting classification scheme accounts for different theoretical approaches for expressing objections and offers a comprehensive perspective on grassroots efforts aimed at stopping offensive or problematic speech on campus.