MSc Thesis Proposal " LADy: Latent Aspect Detection via Backtranslation Augmentation" By: Farinam Hemmati Zadeh

Friday, September 15, 2023 - 11:00

The School of Computer Science is pleased to present…

Thesis Proposal Announcement

LADy: Latent Aspect Detection via Backtranslation Augmentation
MSc Thesis Proposal by: Farinam Hemmati Zadeh
Date: Friday September 15th, 2023
Time: 11:00 AM – 12:00 PM
Location: Essex Hall, Room #122


Within the context of review analytics, aspects are the features of products and services at which customers target their opinions and sentiments. Aspect detection helps product
owners and service providers identify shortcomings and prioritize customers’ needs. Existing methods focus on detecting the surface form of an aspect falling short when aspects are latent in reviews, especially in an informal context like in social posts. In this research work, we propose data augmentation via natural language backtranslation to extract latent occurrences of aspects. We presume that backtranslation (1) can reveal latent aspects because they may not be commonly known in the target language and can be generated through backtranslation; (2) augments context-aware synonymous aspects from a target language to the original language, hence addressing the out-of-vocabulary issue; and (3) helps with the semantic disambiguation of polysemous words and collocations. Through our experiments on well-known aspect detection methods across semeval datasets of restaurant and laptop reviews, we demonstrate that review augmentation via backtranslation yields a steady performance boost in baselines. We further contribute LADy, a benchmark library to support the reproducibility of our research, which is publicly available at

Thesis Committee:

Internal Reader: Dr. Robin Gras
External Reader: Dr. Tanja Collet-Najem, Department of Languages, Literatures and Cultures
Advisor: Dr. Hossein Fani