Perspective-based search: a new paradigm for bursting the information bubble

TL;DR: This paper propose an adversarial nerual netowrk that decomposes a pretrained representation as independent denotation and connotation representations and show that the denotation vectors improve the viewpoint diversity of document rankings.

TL;DR: This study reports on a lab study in which participants gathered information to meet a specific type of LO, and leveraged Anderson and Krathwohl’s (A&K) taxonomy to characterize LOs and pathways.

TL;DR: A game model of bilateral evolution between information platforms and network users and simulates the influence path of key factors on the evolution of both parties’ main strategies is constructed and shows that algorithm recommendation technology is the root of “information cocoons" in the algorithm era.

TL;DR: A scientific quantitative, and visual analysis was conducted on 2101 articles in the field of information cocoons research from 1966 to 2023, finding that Twitter and Facebook are the most studied social media.

TL;DR: This paper survey, classify and comparatively study the various definitions, algorithms and metrics for result diversification.

TL;DR: A great deal of recent work has shown that statistical language models not only achieve superior empirical performance, but also facilitate parameter tuning and provide a more principled way for modeling various kinds of complex and non-traditional retrieval problems.

TL;DR: This work examines the relationship between the numbers of supporting and challenging items in a collection of political opinion items and readers' satisfaction, and evaluates whether simple presentation techniques such as highlighting agreeable items or showing them first can increase satisfaction when fewer agreeable items are present.

TL;DR: This paper presents NewsCube, a novel Internet news service aiming at mitigating the effect of media bias, which is the first to develop a news service as a solution and study its effect.