Embedding-Based Approaches to Hyperpartisan News Detection

Karthik Mohan

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arXiv · 2501.01370

Embedding-Based Approaches to Hyperpartisan News Detection

Karthik Mohan

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Abstract

In this report, I describe the systems in which the objective is to determine whether a given news article could be considered as hyperpartisan. Hyperpartisan news takes an extremely polarized political standpoint with an intention of creating political divide among the public. Several approaches, including n-grams, sentiment analysis, as well as sentence and document representations using pre-tained ELMo models were used. The best system is using LLMs for embedding generation achieving an accuracy of around 92% over the previously best system using pre-trained ELMo with Bidirectional LSTM which achieved an accuracy of around 83% through 10-fold cross-validation.

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Karthik Mohan. 2025-01-02. Embedding-Based Approaches to Hyperpartisan News Detection. https://arxiv.org/abs/2501.01370

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