Related papers: Tanbih: Get To Know What You Are Reading
Detecting important events in high volume news streams is an important task for a variety of purposes.The volume and rate of online news increases the need for automated event detection methods thatcan operate in real time. In this paper we…
Investigating efficiently the data collected from a system's activity can help to detect malicious attempts and better understand the context behind past incident occurrences. Nowadays, several solutions can be used to monitor system…
We propose a novel training and inference method for detecting political bias in long text content such as newspaper opinion articles. Obtaining long text data and annotations at sufficient scale for training is difficult, but it is…
An Unreliable news is any piece of information which is false or misleading, deliberately spread to promote political, ideological and financial agendas. Recently the problem of unreliable news has got a lot of attention as the number…
With the explosive growth of online social media, the ancient problem of information disorders interfering with news diffusion has surfaced with a renewed intensity threatening our democracies, public health, and news outlets' credibility.…
An ability to infer the political leaning of social media users can help in gathering opinion polls thereby leading to a better understanding of public opinion. While there has been a body of research attempting to infer the political…
Disinformation and false content produced by generative AI pose a significant challenge for journalists and fact-checkers who must rapidly verify digital media information. While there is an abundance of NLP models for detecting credibility…
News agencies publish news on their websites all over the world. Moreover, creating novel corpuses is necessary to bring natural processing to new domains. Textual processing of online news is challenging in terms of the strategy of…
Polarized topics often spark discussion and debate on social media. Recent studies have shown that polarized debates have a specific clustered structure in the endorsement net- work, which indicates that users direct their endorsements…
Online social media provide multiple ways to find interesting content. One important method is highlighting content recommended by user's friends. We examine this process on one such site, the news aggregator Digg. With a stochastic model…
When a news article describes immigration as an "economic burden" or a "humanitarian crisis," it selectively emphasizes certain aspects of the issue. Although \textit{framing} shapes how the public interprets such issues, audiences do not…
Narratives are fundamental to our understanding of the world, providing us with a natural structure for knowledge representation over time. Computational narrative extraction is a subfield of artificial intelligence that makes heavy use of…
The proliferation of online debate platforms and social media has led to an unprecedented volume of argumentative content on controversial topics from multiple perspectives. While this wealth of perspectives offers opportunities for…
Many users reading online articles in various magazines may suffer considerable difficulty in distinguishing the implicit intents in texts. In this work, we focus on automatically recognizing the political intents of a given online…
The ability to quantify incivility online, in news and in congressional debates, is of great interest to political scientists. Computational tools for detecting online incivility for English are now fairly accessible and potentially could…
The purpose of an argumentative text is to support a certain conclusion. Yet, they are often omitted, expecting readers to infer them rather. While appropriate when reading an individual text, this rhetorical device limits accessibility…
In recent years, malicious information had an explosive growth in social media, with serious social and political backlashes. Recent important studies, featuring large-scale analyses, have produced deeper knowledge about this phenomenon,…
We present a new computational framework for detecting and structuring manipulative political narratives. A task that became more important due to the shift of political discussions to social media. One of the primary challenges thereby is…
News recommender systems are devised to alleviate the information overload, attracting more and more researchers' attention in recent years. The lack of a dedicated learner-oriented news recommendation toolkit hinders the advancement of…
Quantification of the political leaning of online news articles can aid in understanding the dynamics of political ideology in social groups and measures to mitigating them. However, predicting the accurate political leaning of a news…