相关论文: NeMig -- A Bilingual News Collection and Knowledge…
News recommender systems are used by online news providers to alleviate information overload and to provide personalized content to users. However, algorithmic news curation has been hypothesized to create filter bubbles and to intensify…
Digital news platforms use news recommenders as the main instrument to cater to the individual information needs of readers. Despite an increasingly language-diverse online community, in which many Internet users consume news in multiple…
Social media has a misinformation problem, and counterspeech -- fighting bad speech with more speech -- has been an ineffective solution. Here, we argue that bridging-based ranking -- an algorithmic approach to promoting content favored by…
Accurate news representation is critical for news recommendation. Most of existing news representation methods learn news representations only from news texts while ignore the visual information in news like images. In fact, users may click…
Nowadays, artificial intelligence algorithms are used for targeted and personalized content distribution in the large scale as part of the intense competition for attention in the digital media environment. Unfortunately, targeted…
In this study, we applied the ``personalized diversity nudge framework'' with the goal of expanding user reading coverage in terms of news locality (i.e., domestic and world news). We designed a novel topic-locality dual calibration…
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.…
News recommender systems (NRs) have been shown to shape public discourse and to enforce behaviors that have a critical, oftentimes detrimental effect on democracies. Earlier research on the impact of media bias has revealed their strong…
Online platforms have transformed the way in which individuals access and interact with news, with a high degree of trust particularly placed in search engine results. We use web tracked behavioral data across a 2-month period and analyze…
Research on infodemics, i.e., the rapid spread of (mis)information related to a hazardous event, such as the COVID-19 pandemic, requires the integration of a multiplicity of scientific disciplines. The dynamics emerging from infodemics have…
The spread of media bias is a significant concern as political discourse shapes beliefs and opinions. Addressing this challenge computationally requires improved methods for interpreting news. While large language models (LLMs) can scale…
News recommenders help users to find relevant online content and have the potential to fulfill a crucial role in a democratic society, directing the scarce attention of citizens towards the information that is most important to them.…
The suggestions generated by most existing recommender systems are known to suffer from a lack of diversity, and other issues like popularity bias. As a result, they have been observed to promote well-known "blockbuster" items, and to…
News recommendation (NR) is essential for online news services. Existing NR methods typically adopt a news-user representation learning framework, facing two potential limitations. First, in news encoder, single candidate news encoding…
Research shows news consumption differs across demographics, yet little is known about non-mainstream audiences, especially in relation to local media. Our study addresses this gap by examining how French-speaking migrants in a mid-size…
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…
In the recent political climate, the topic of news quality has drawn attention both from the public and the academic communities. The growing distrust of traditional news media makes it harder to find a common base of accepted truth. In…
The rise of the social media sites, such as blogs, wikis, Digg and Flickr among others, underscores the transformation of the Web to a participatory medium in which users are collaboratively creating, evaluating and distributing…
With the spread of false and misleading information in current news, many algorithmic tools have been introduced with the aim of assessing bias and reliability in written content. However, there has been little work exploring how effective…
There is a soaring interest in the news recommendation research scenario due to the information overload. To accurately capture users' interests, we propose to model multi-modal features, in addition to the news titles that are widely used…