Sentiment, Emotion & Aspects
Early work on aspect extraction, emotion analysis and corpora for low-resource languages.
- 2017
Multi-domain Aspect Extraction using Support Vector Machines
Feature-engineered one-vs-rest SVM beats SemEval-2016 best on both domains (F1 74.2 / 52.2)
ROCLING · Co-author - 2018
Aspect Extraction from Customer Reviews Using Convolutional Neural Networks
Multi-kernel CNN with theory-sized layers; best restaurant F1 (76.0) at the time
ICTer · Co-author -
DataSEARCH at IEST 2018: Multiple Word Embedding Based Models for Implicit Emotion Classification of Tweets with Deep Learning
Stacked LSTM-CNN over 6 embeddings for implicit emotion; macro-F1 68.1, ranked 8th
WASSA @ EMNLP · First author - 2019
A Hybrid Approach for Aspect Extraction from Customer Reviews
CNN + SVM probability ensemble sets best F1 on SemEval-2016 (77.2 / 54.5)
ICTer Journal · First author -
ACTSEA: Annotated Corpus for Tamil & Sinhala Emotion Analysis
First Tamil/Sinhala emotion corpus (~900k tweets) via morphological keyword expansion
MERCon · Co-author - 2020
Exploring Deep Neural Networks and Transfer Learning for Analyzing Emotions in Tweets
LSTM-CNN + DeepMoji/sentiment-neuron transfer ≈ SOTA emotion intensity (r 0.798) + SHAP explanations
arXiv · First author