1 code implementation • 17 Jan 2024 • Aiqi Jiang, Arkaitz Zubiaga
This survey presents a systematic and comprehensive exploration of Cross-Lingual Transfer Learning (CLTL) techniques in offensive language detection in social media.
no code implementations • 20 Dec 2022 • Wenjie Yin, Vibhor Agarwal, Aiqi Jiang, Arkaitz Zubiaga, Nishanth Sastry
During training, the model associates annotators with their label choices given a piece of text; during evaluation, when label information is not available, the model predicts the aggregated label given by the participating annotators by utilising the learnt association.
1 code implementation • 15 Nov 2022 • Aiqi Jiang, Arkaitz Zubiaga
The goal of sexism detection is to mitigate negative online content targeting certain gender groups of people.
no code implementations • 6 Aug 2021 • Aiqi Jiang, Arkaitz Zubiaga
Most hate speech detection research focuses on a single language, generally English, which limits their generalisability to other languages.
no code implementations • 6 Aug 2021 • Aiqi Jiang, Xiaohan Yang, Yang Liu, Arkaitz Zubiaga
We propose the first Chinese sexism dataset -- Sina Weibo Sexism Review (SWSR) dataset --, as well as a large Chinese lexicon SexHateLex made of abusive and gender-related terms.
no code implementations • 14 Nov 2018 • Aiqi Jiang, Arkaitz Zubiaga
Online review platforms are a popular way for users to post reviews by expressing their opinions towards a product or service, as well as they are valuable for other users and companies to find out the overall opinions of customers.
no code implementations • 22 Jan 2018 • Arkaitz Zubiaga, Aiqi Jiang
Our dataset represents a realistic scenario with a real distribution of true, commemorative and false stories, which we release for further use as a benchmark in future research.