26 citations · 39 across the 4 of their papers we have counts for
10 papers
On Natural Language User Profiles for Transparent and Scrutable Recommendation
Filip Radlinski, Krisztian Balog, Fernando Diaz +2
Natural interaction with recommendation and personalized search systems has received tremendous attention in recent years. We focus on the challenge of supporting people's understa…
Augmenting the User-Item Graph with Textual Similarity Models
Federico López, Martin Scholz, Jessica Yung +3
This paper introduces a simple and effective form of data augmentation for recommender systems. A paraphrase similarity model is applied to widely available textual data, such as r…
Civil Rephrases Of Toxic Texts With Self-Supervised Transformers
Leo Laugier, John Pavlopoulos, Jeffrey Sorensen +1
Platforms that support online commentary, from social networks to news sites, are increasingly leveraging machine learning to assist their moderation efforts. But this process does…
Six Attributes of Unhealthy Conversation
Ilan Price, Jordan Gifford-Moore, Jory Fleming +6
We present a new dataset of approximately 44000 comments labeled by crowdworkers. Each comment is labelled as either 'healthy' or 'unhealthy', in addition to binary labels for the…
Toxicity Detection: Does Context Really Matter?
John Pavlopoulos, Jeffrey Sorensen, Lucas Dixon +2
Moderation is crucial to promoting healthy on-line discussions. Although several `toxicity' detection datasets and models have been published, most of them ignore the context of th…
Classifying Constructive Comments
Varada Kolhatkar, Nithum Thain, Jeffrey Sorensen +2
We introduce the Constructive Comments Corpus (C3), comprised of 12,000 annotated news comments, intended to help build new tools for online communities to improve the quality of t…