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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 toward 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\u2019s 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.<\/jats:p>","DOI":"10.1145\/3745769","type":"journal-article","created":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T11:59:42Z","timestamp":1750852782000},"page":"1-53","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Behind the Counter: Exploring Motivations and Barriers of Online Counterspeech Writing"],"prefix":"10.1145","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7520-7503","authenticated-orcid":false,"given":"Kaike","family":"Ping","sequence":"first","affiliation":[{"name":"Computer Science, Virginia Tech, Blacksburg, Virginia, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-0527-2660","authenticated-orcid":false,"given":"Anisha","family":"Kumar","sequence":"additional","affiliation":[{"name":"Computer Science, Virginia Tech, Blacksburg, Virginia, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2679-3344","authenticated-orcid":false,"given":"Xiaohan","family":"Ding","sequence":"additional","affiliation":[{"name":"Computer Science, Virginia Tech, Blacksburg, Virginia, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0961-4397","authenticated-orcid":false,"given":"Eugenia H.","family":"Rho","sequence":"additional","affiliation":[{"name":"Computer Science, Virginia Tech, Blacksburg, Virginia, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,10,14]]},"reference":[{"key":"e_1_3_3_2_2","unstructured":"A Better ChatGPT App. 2023. 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