Stance Detection in Web and Social Media: A Comparative Study

07/12/2020
by   Shalmoli Ghosh, et al.
0

Online forums and social media platforms are increasingly being used to discuss topics of varying polarities where different people take different stances. Several methodologies for automatic stance detection from text have been proposed in literature. To our knowledge, there has not been any systematic investigation towards their reproducibility, and their comparative performances. In this work, we explore the reproducibility of several existing stance detection models, including both neural models and classical classifier-based models. Through experiments on two datasets – (i) the popular SemEval microblog dataset, and (ii) a set of health-related online news articles – we also perform a detailed comparative analysis of various methods and explore their shortcomings. Implementations of all algorithms discussed in this paper are available at https://github.com/prajwal1210/Stance-Detection-in-Web-and-Social-Media.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/08/2023

UQ at #SMM4H 2023: ALEX for Public Health Analysis with Social Media

As social media becomes increasingly popular, more and more activities r...
research
09/02/2023

Enable people to identify science news based on retracted articles on social media

For many people, social media is an important way to consume news on imp...
research
09/08/2019

How much research output from India gets social media attention?

Scholarly articles are now increasingly being mentioned and discussed in...
research
06/10/2019

Automatically Identifying Complaints in Social Media

Complaining is a basic speech act regularly used in human and computer m...
research
01/14/2020

Vocabulary-based Method for Quantifying Controversy in Social Media

Identifying controversial topics is not only interesting from a social p...
research
09/28/2022

Signed Latent Factors for Spamming Activity Detection

Due to the increasing trend of performing spamming activities (e.g., Web...
research
02/06/2023

It's about Time: Rethinking Evaluation on Rumor Detection Benchmarks using Chronological Splits

New events emerge over time influencing the topics of rumors in social m...

Please sign up or login with your details

Forgot password? Click here to reset