Stance detection in tweets: A topic modeling approach supporting explainability

Article Computer Science, Artificial Intelligence

A novel approach to stance detection in social media tweets by fusing ranked lists and sentiments

Abdulrahman I. Al-Ghadir et al.

Summary: This study introduces a novel approach for identifying the stance of Twitter authors and implements it through a three-phase process. The performance is evaluated using six different classifiers, achieving the best performance with the weighted K-NN classifier.

INFORMATION FUSION (2021)

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Article Computer Science, Information Systems

When classification accuracy is not enough: Explaining news credibility assessment

Piotr Przybyla et al.

Summary: The credibility of online news is a major concern that impacts readers and society negatively. By using two machine learning methods, researchers aim to improve credibility assessment explanations and enhance reader confidence. The adapted neural classifier outperformed the stylometric classifier, and users showed increased accuracy and confidence in their assessments after interacting with the tool.

INFORMATION PROCESSING & MANAGEMENT (2021)

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Article Social Issues

A novel approach for efficient stance detection in online social networks with metaheuristic optimization *

Umit Can et al.

Summary: Social networks have been an important topic in various fields since the 19th and 20th centuries, but with advances in computer technology, traditional networks have evolved into online social networks, introducing new problems and solutions. Researchers are constantly developing new methods or enhancing existing ones to improve the performance of social network analysis.

TECHNOLOGY IN SOCIETY (2021)

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Article Computer Science, Information Systems