News recommender system: a review of recent progress, challenges, and opportunities
Nowadays, more and more news readers read news online where they have access to
millions of news articles from multiple sources. In order to help users find the right and …
millions of news articles from multiple sources. In order to help users find the right and …
The unified framework of media diversity: A systematic literature review
How to study media diversity has become a major concern in today's media landscape.
Many expect that algorithmic filtering and a shift of audiences from legacy media to new …
Many expect that algorithmic filtering and a shift of audiences from legacy media to new …
User perceptions of algorithmic decisions in the personalized AI system: Perceptual evaluation of fairness, accountability, transparency, and explainability
D Shin - Journal of Broadcasting & Electronic Media, 2020 - Taylor & Francis
With the growing presence of algorithms and their far-reaching effects, artificial intelligence
(AI) will be mainstream trends any time soon. Despite this surging popularity, little is known …
(AI) will be mainstream trends any time soon. Despite this surging popularity, little is known …
Neural news recommendation with long-and short-term user representations
Personalized news recommendation is important to help users find their interested news
and improve reading experience. A key problem in news recommendation is learning …
and improve reading experience. A key problem in news recommendation is learning …
News recommender systems–Survey and roads ahead
More and more people read the news online, eg, by visiting the websites of their favorite
newspapers or by navigating the sites of news aggregators. However, the abundance of …
newspapers or by navigating the sites of news aggregators. However, the abundance of …
Personalized news recommendation: Methods and challenges
Personalized news recommendation is important for users to find interesting news
information and alleviate information overload. Although it has been extensively studied …
information and alleviate information overload. Although it has been extensively studied …
Beyond user experience: What constitutes algorithmic experiences?
Algorithms are progressively transforming human experience, especially, the interaction with
businesses, governments, education, and entertainment. As a result, people are growingly …
businesses, governments, education, and entertainment. As a result, people are growingly …
Fine-grained interest matching for neural news recommendation
Personalized news recommendation is a critical technology to improve users' online news
reading experience. The core of news recommendation is accurate matching between user's …
reading experience. The core of news recommendation is accurate matching between user's …
How do users interact with algorithm recommender systems? The interaction of users, algorithms, and performance
D Shin - Computers in human behavior, 2020 - Elsevier
Although algorithms have been widely used to deliver useful applications and services, it is
unclear how users actually experience and interact with algorithm-driven services. This …
unclear how users actually experience and interact with algorithm-driven services. This …
Embodying algorithms, enactive artificial intelligence and the extended cognition: You can see as much as you know about algorithm
D Shin - Journal of Information Science, 2023 - journals.sagepub.com
The recent proliferation of artificial intelligence (AI) gives rise to questions on how users
interact with AI services and how algorithms embody the values of users. Despite the …
interact with AI services and how algorithms embody the values of users. Despite the …