activity
20172020
most citedBirds of a Feather Flock Together: Satirical News Detection via Language Model Differentiation

24 citations · 37 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL202024 cited

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…

cs.CR20202 cited

Less is More: Exploiting Social Trust to Increase the Effectiveness of a Deception Attack

Shahryar Baki, Rakesh M. Verma, Arjun Mukherjee +1

Cyber attacks such as phishing, IRS scams, etc., still are successful in fooling Internet users. Users are the last line of defense against these attacks since attackers seem to al…

cs.CL2020

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…

cs.CL2019

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…

cs.CL20175 cited

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…

cs.CL20176 cited

Detecting Sockpuppets in Deceptive Opinion Spam

Marjan Hosseinia, Arjun Mukherjee

This paper explores the problem of sockpuppet detection in deceptive opinion spam using authorship attribution and verification approaches. Two methods are explored. The first is a…