A taxonomy and review of generalization research in NLP
The ability to generalize well is one of the primary desiderata for models of natural language
processing (NLP), but what 'good generalization'entails and how it should be evaluated is …
processing (NLP), but what 'good generalization'entails and how it should be evaluated is …
The media bias taxonomy: A systematic literature review on the forms and automated detection of media bias
The way the media presents events can significantly affect public perception, which in turn
can alter people's beliefs and views. Media bias describes a one-sided or polarizing …
can alter people's beliefs and views. Media bias describes a one-sided or polarizing …
State-of-the-art generalisation research in NLP: a taxonomy and review
The ability to generalise well is one of the primary desiderata of natural language
processing (NLP). Yet, what'good generalisation'entails and how it should be evaluated is …
processing (NLP). Yet, what'good generalisation'entails and how it should be evaluated is …
[HTML][HTML] Evaluating the generalisability of neural rumour verification models
Research on automated social media rumour verification, the task of identifying the veracity
of questionable information circulating on social media, has yielded neural models …
of questionable information circulating on social media, has yielded neural models …
Fine-grained classification of political bias in German news: A data set and initial experiments
We present a data set consisting of German news articles labeled for political bias on a five-
point scale in a semi-supervised way. While earlier work on hyperpartisan news detection …
point scale in a semi-supervised way. While earlier work on hyperpartisan news detection …
Unlocking Bias Detection: Leveraging Transformer-Based Models for Content Analysis
S Raza, O Bamgbose, V Chatrath… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Bias detection in text is crucial for combating the spread of negative stereotypes,
misinformation, and biased decision-making. Traditional language models frequently face …
misinformation, and biased decision-making. Traditional language models frequently face …
Unsupervised domain-agnostic fake news detection using multi-modal weak signals
The emergence of social media as one of the main platforms for people to access news has
enabled the wide dissemination of fake news, having serious impacts on society. Thus, it is …
enabled the wide dissemination of fake news, having serious impacts on society. Thus, it is …
[HTML][HTML] RESPECT: A framework for promoting inclusive and respectful conversations in online communications
Toxicity and bias in online conversations hinder respectful interactions, leading to issues
such as harassment and discrimination. While advancements in natural language …
such as harassment and discrimination. While advancements in natural language …
Probing spurious correlations in popular event-based rumor detection benchmarks
As social media becomes a hotbed for the spread of misinformation, the crucial task of rumor
detection has witnessed promising advances fostered by open-source benchmark datasets …
detection has witnessed promising advances fostered by open-source benchmark datasets …
Incorporating Accuracy and Diversity in a News Recommender System
There are certain challenges in news recommender systems that arise due to changing
users' preferences over dynamically generated news articles. It is important to expose users …
users' preferences over dynamically generated news articles. It is important to expose users …