Behind the Counter: Exploring the Motivations and Barriers of Online Counterspeech Writing
- URL: http://arxiv.org/abs/2403.17116v1
- Date: Mon, 25 Mar 2024 18:56:35 GMT
- Title: Behind the Counter: Exploring the Motivations and Barriers of Online Counterspeech Writing
- Authors: Kaike Ping, Anisha Kumar, Xiaohan Ding, Eugenia Rho,
- Abstract summary: Having been a target of online hate is a key driver of frequent online counterspeech engagement.
People differ in their motivations and barriers towards engaging in online counterspeech across different demographic groups.
- Score: 6.790819952175892
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Current research mainly explores the attributes and impact of online counterspeech, leaving a gap in understanding of who engages in online counterspeech or what motivates or deters users from participating. To investigate this, we surveyed 458 English-speaking U.S. participants, analyzing key motivations and barriers underlying online counterspeech engagement. We presented each participant with three hate speech examples from a set of 900, spanning race, gender, religion, sexual orientation, and disability, and requested counterspeech responses. Subsequent questions assessed their satisfaction, perceived difficulty, and the effectiveness of their counterspeech. Our findings show that having been a target of online hate is a key driver of frequent online counterspeech engagement. People differ in their motivations and barriers towards engaging in online counterspeech across different demographic groups. Younger individuals, women, those with higher education levels, and regular witnesses to online hate are more reluctant to engage in online counterspeech due to concerns around public exposure, retaliation, and third-party harassment. Varying motivation and barriers in counterspeech engagement also shape how individuals view their own self-authored counterspeech and the difficulty experienced writing it. Additionally, our work explores people's willingness to use AI technologies like ChatGPT for counterspeech writing. Through this work we introduce a multi-item scale for understanding counterspeech motivation and barriers and a more nuanced understanding of the factors shaping online counterspeech engagement.
Related papers
- CounterQuill: Investigating the Potential of Human-AI Collaboration in Online Counterspeech Writing [6.929003593008481]
We introduce CounterQuill, an AI-mediated system that assists users in composing effective and empathetic counterspeech.
CounterQuill provides a three-step process: (1) a learning session to help users understand hate speech and counterspeech; (2) a brainstorming session that guides users in identifying key elements of hate speech and exploring counterspeech strategies; and (3) a co-writing session that enables users to draft and refine their counterspeech with CounterQuill.
arXiv Detail & Related papers (2024-10-03T22:29:20Z) - Moshi: a speech-text foundation model for real-time dialogue [78.88479749811376]
Current systems for spoken dialogue rely on pipelines independent voice activity detection and text-to-speech.
We show how Moshi Moshi can provide streaming speech recognition and text-to-speech.
Our resulting model is first real-time full spoken large language model modality.
arXiv Detail & Related papers (2024-09-17T17:55:39Z) - Demarked: A Strategy for Enhanced Abusive Speech Moderation through Counterspeech, Detoxification, and Message Management [71.99446449877038]
We propose a more comprehensive approach called Demarcation scoring abusive speech based on four aspect -- (i) severity scale; (ii) presence of a target; (iii) context scale; (iv) legal scale.
Our work aims to inform future strategies for effectively addressing abusive speech online.
arXiv Detail & Related papers (2024-06-27T21:45:33Z) - NLP for Counterspeech against Hate: A Survey and How-To Guide [11.696212004806263]
We provide a guide for doing research on counterspeech, by describing - with detailed examples - the steps to undertake.
We discuss open challenges and future directions of counterspeech research in NLP.
arXiv Detail & Related papers (2024-03-29T10:32:44Z) - Hatred Stems from Ignorance! Distillation of the Persuasion Modes in Countering Conversational Hate Speech [0.0]
This study distills persuasion modes into reason, emotion, and credibility.
It evaluates their use in two types of conversation interactions: closed (multi-turn) and open (single-turn) concerning racism, sexism, and religious bigotry.
arXiv Detail & Related papers (2024-03-18T07:20:35Z) - Persua: A Visual Interactive System to Enhance the Persuasiveness of
Arguments in Online Discussion [52.49981085431061]
Enhancing people's ability to write persuasive arguments could contribute to the effectiveness and civility in online communication.
We derived four design goals for a tool that helps users improve the persuasiveness of arguments in online discussions.
Persua is an interactive visual system that provides example-based guidance on persuasive strategies to enhance the persuasiveness of arguments.
arXiv Detail & Related papers (2022-04-16T08:07:53Z) - E-ffective: A Visual Analytic System for Exploring the Emotion and
Effectiveness of Inspirational Speeches [57.279044079196105]
E-ffective is a visual analytic system allowing speaking experts and novices to analyze both the role of speech factors and their contribution in effective speeches.
Two novel visualizations include E-spiral (that shows the emotional shifts in speeches in a visually compact way) and E-script (that connects speech content with key speech delivery information.
arXiv Detail & Related papers (2021-10-28T06:14:27Z) - Countering Online Hate Speech: An NLP Perspective [34.19875714256597]
Online toxicity - an umbrella term for online hateful behavior - manifests itself in forms such as online hate speech.
The rising mass communication through social media further exacerbates the harmful consequences of online hate speech.
This paper presents a holistic conceptual framework on hate-speech NLP countering methods along with a thorough survey on the current progress of NLP for countering online hate speech.
arXiv Detail & Related papers (2021-09-07T08:48:13Z) - Fragments of the Past: Curating Peer Support with Perpetrators of
Domestic Violence [88.37416552778178]
We report on a ten-month study where we worked with six support workers and eighteen perpetrators in the design and deployment of Fragments of the Past.
We share how crafting digitally-augmented artefacts - 'fragments' - of experiences of desisting from violence can translate messages for motivation and rapport between peers.
These insights provide the basis for practical considerations for future network design with challenging populations.
arXiv Detail & Related papers (2021-07-09T22:57:43Z) - Speaker De-identification System using Autoencoders and Adversarial
Training [58.720142291102135]
We propose a speaker de-identification system based on adversarial training and autoencoders.
Experimental results show that combining adversarial learning and autoencoders increase the equal error rate of a speaker verification system.
arXiv Detail & Related papers (2020-11-09T19:22:05Z) - Impact and dynamics of hate and counter speech online [0.0]
Citizen-generated counter speech is a promising way to fight hate speech and promote peaceful, non-polarized discourse.
We analyze 180,000 political conversations that took place on German Twitter over four years.
arXiv Detail & Related papers (2020-09-16T01:43:28Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.