← Authors

Svetlana Kiritchenko

35 papers · 2011–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (14) 🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (34) πŸ”¬ Deep Specialist (11) 🀝 Dynamic Duo (16) 🧬 Topic Evolution ⚑ Prolific Year (5) πŸ’Ž Century Club (35) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (92) πŸ”₯ Unstoppable (13) ❓ The Questioner (3)

Conferences

NAACL (11) ACL (10) SEMEVAL (8) EMNLP (3) COLING (1) EACL (1) IJCNLP (1)

Top co-authors

Isar Nejadgholi (16) Saif Mohammad (12) Kathleen C. Fraser (11) Kathleen Fraser (8) Xiaodan Zhu (5) Esma Balkir (5) Colin Cherry (3) Hillary Dawkins (3) Mohammad Salameh (3) Anna Kerkhof (2)

Keywords

sentiment analysis (7) text classification (6) bias detection (5) large language model (4) hate speech detection (3) social media analysis (3) bias mitigation (3) social media (3) abusive language detection (3) stereotype detection (3) domain generalization (3) bias evaluation (2) toxic language detection (2) natural language processing (2) concept-based explanation (2) semantic embedding (2) unsupervised learning (2) model interpretability (2) social bia (2) topic modeling (1)

Papers

When Detection Fails: The Power of Fine-Tuned Models to Generate Human-Like Social Media Text ACL 2025
Uncovering Bias in Large Vision-Language Models at Scale with Counterfactuals NAACL 2025
Tackling Social Bias against the Poor: a Dataset and a Taxonomy on Aporophobia NAACL 2025
Fine-Tuning Lowers Safety and Disrupts Evaluation Consistency ACL 2025
How Does Stereotype Content Differ across Data Sources? NAACL 2024
Challenging Negative Gender Stereotypes: A Study on the Effectiveness of Automated Counter-Stereotypes COLING 2024
Examining Gender and Racial Bias in Large Vision–Language Models Using a Novel Dataset of Parallel Images EACL 2024
Adaptable Moral Stances of Large Language Models on Sexist Content: Implications for Society and Gender Discourse EMNLP 2024
The Crime of Being Poor: Associations between Crime and Poverty on Social Media in Eight Countries NAACL 2024
Aporophobia: An Overlooked Type of Toxic Language Targeting the Poor ACL 2023
What Makes a Good Counter-Stereotype? Evaluating Strategies for Automated Responses to Stereotypical Text ACL 2023
Concept-Based Explanations to Test for False Causal Relationships Learned by Abusive Language Classifiers ACL 2023
Improving Generalizability in Implicitly Abusive Language Detection with Concept Activation Vectors ACL 2022
Towards Procedural Fairness: Uncovering Biases in How a Toxic Language Classifier Uses Sentiment Information EMNLP 2022
Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models NAACL 2022
Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detection NAACL 2022
Does Moral Code have a Moral Code? Probing Delphi’s Moral Philosophy NAACL 2022
Understanding and Countering Stereotypes: A Computational Approach to the Stereotype Content Model ACL 2021
Understanding and Countering Stereotypes: A Computational Approach to the Stereotype Content Model IJCNLP 2021
On Cross-Dataset Generalization in Automatic Detection of Online Abuse EMNLP 2020
Big BiRD: A Large, Fine-Grained, Bigram Relatedness Dataset for Examining Semantic Composition NAACL 2019
DeepMiner at SemEval-2018 Task 1: Emotion Intensity Recognition Using Deep Representation Learning SEMEVAL 2018
SemEval-2018 Task 1: Affect in Tweets SEMEVAL 2018
Best-Worst Scaling More Reliable than Rating Scales: A Case Study on Sentiment Intensity Annotation ACL 2017
Capturing Reliable Fine-Grained Sentiment Associations by Crowdsourcing and Best–Worst Scaling NAACL 2016
Sentiment Composition of Words with Opposing Polarities NAACL 2016
SemEval-2016 Task 6: Detecting Stance in Tweets SEMEVAL 2016
SemEval-2016 Task 7: Determining Sentiment Intensity of English and Arabic Phrases SEMEVAL 2016
Sentiment after Translation: A Case-Study on Arabic Social Media Posts NAACL 2015
SemEval-2015 Task 10: Sentiment Analysis in Twitter SEMEVAL 2015
NRC-Canada-2014: Detecting Aspects and Sentiment in Customer Reviews SEMEVAL 2014
An Empirical Study on the Effect of Negation Words on Sentiment ACL 2014
NRC-Canada-2014: Recent Improvements in the Sentiment Analysis of Tweets SEMEVAL 2014
NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets SEMEVAL 2013
Lexically-Triggered Hidden Markov Models for Clinical Document Coding ACL 2011