24 citations · 37 across the 6 of their papers we have counts for
7 papers · 1 filter
Multi-Aspect Sentiment Analysis with Latent Sentiment-Aspect Attribution
Yifan Zhang, Fan Yang, Marjan Hosseinia +1
In this paper, we introduce a new framework called the sentiment-aspect attribution module (SAAM). SAAM works on top of traditional neural networks and is designed to address the p…
Birds of a Feather Flock Together: Satirical News Detection via Language Model Differentiation
Yigeng Zhang, Fan Yang, Yifan Zhang +2
Satirical news is regularly shared in modern social media because it is entertaining with smartly embedded humor. However, it can be harmful to society because it can sometimes be…
Stance Prediction for Contemporary Issues: Data and Experiments
Marjan Hosseinia, Eduard Dragut, Arjun Mukherjee
We investigate whether pre-trained bidirectional transformers with sentiment and emotion information improve stance detection in long discussions of contemporary issues. As a part…
Aspect Specific Opinion Expression Extraction using Attention based LSTM-CRF Network
Abhishek Laddha, Arjun Mukherjee
Opinion phrase extraction is one of the key tasks in fine-grained sentiment analysis. While opinion expressions could be generic subjective expressions, aspect specific opinion exp…
Experiments with Neural Networks for Small and Large Scale Authorship Verification
Marjan Hosseinia, Arjun Mukherjee
We propose two models for a special case of authorship verification problem. The task is to investigate whether the two documents of a given pair are written by the same author. We…
Satirical News Detection and Analysis using Attention Mechanism and Linguistic Features
Fan Yang, Arjun Mukherjee, Eduard Dragut
Satirical news is considered to be entertainment, but it is potentially deceptive and harmful. Despite the embedded genre in the article, not everyone can recognize the satirical c…