activity
20192022
most citedSeq2Emo for Multi-label Emotion Classification Based on Latent Variable Chains Transformation

18 citations · 34 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL20223 cited

Depression Symptoms Modelling from Social Media Text: A Semi-supervised Learning Approach

Nawshad Farruque, Randy Goebel, Sudhakar Sivapalan +1

A fundamental component of user-level social media language based clinical depression modelling is depression symptoms detection (DSD). Unfortunately, there does not exist any DSD…

cs.CL2021

A comprehensive empirical analysis on cross-domain semantic enrichment for detection of depressive language

Nawshad Farruque, Randy Goebel, Osmar Zaiane

We analyze the process of creating word embedding feature representations designed for a learning task when annotated data is scarce, for example, in depressive language detection…

cs.CL2021

STEP-EZ: Syntax Tree guided semantic ExPlanation for Explainable Zero-shot modeling of clinical depression symptoms from text

Nawshad Farruque, Randy Goebel, Osmar Zaiane +1

We focus on exploring various approaches of Zero-Shot Learning (ZSL) and their explainability for a challenging yet important supervised learning task notorious for training data s…

cs.LG20215 cited

Basic and Depression Specific Emotion Identification in Tweets: Multi-label Classification Experiments

Nawshad Farruque, Chenyang Huang, Osmar Zaiane +1

In this paper, we present empirical analysis on basic and depression specific multi-emotion mining in Tweets with the help of state of the art multi-label classifiers. We choose ou…

cs.AI20208 cited

A multi-component framework for the analysis and design of explainable artificial intelligence

S. Atakishiyev, H. Babiker, N. Farruque +6

The rapid growth of research in explainable artificial intelligence (XAI) follows on two substantial developments. First, the enormous application success of modern machine learnin…

cs.CL201918 cited

Seq2Emo for Multi-label Emotion Classification Based on Latent Variable Chains Transformation

Chenyang Huang, Amine Trabelsi, Xuebin Qin +2

Emotion detection in text is an important task in NLP and is essential in many applications. Most of the existing methods treat this task as a problem of single-label multi-class t…