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Social media have quickly become a prevalent channel to access information, spread ideas, and influence opinions. However, it has been suggested that social and algorithmic filtering may cause exposure to less diverse points of view, and…

Social and Information Networks · Computer Science 2015-10-30 Dimitar Nikolov , Diego F. M. Oliveira , Alessandro Flammini , Filippo Menczer

Many projects (both practical and academic) have designed algorithms to match users to content they will enjoy under the assumption that user's preferences and opinions do not change with the content they see. Evidence suggests that…

Machine Learning · Computer Science 2022-05-27 Sarah Dean , Jamie Morgenstern

The paper develops a stochastic model of drift in human beliefs that shows that today's sheer volume of accessible information, combined with consumers' confirmation bias and natural preference to more outlying content, necessarily lead to…

Social and Information Networks · Computer Science 2021-01-19 Chao Xu , Jinyang Li , Tarek Abdelzaher , Heng Ji , Boleslaw K. Szymanski , John Dellaverson

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…

Computers and Society · Computer Science 2019-09-05 Bibek Paudel , Abraham Bernstein

It remains unknown whether personalized recommendations increase or decrease the diversity of content people consume. We present results from a randomized field experiment on Spotify testing the effect of personalized recommendations on…

Social and Information Networks · Computer Science 2020-03-19 David Holtz , Benjamin Carterette , Praveen Chandar , Zahra Nazari , Henriette Cramer , Sinan Aral

Our consumption of online information is mediated by filtering, ranking, and recommendation algorithms that introduce unintentional biases as they attempt to deliver relevant and engaging content. It has been suggested that our reliance on…

Social and Information Networks · Computer Science 2020-10-07 Dimitar Nikolov , Mounia Lalmas , Alessandro Flammini , Filippo Menczer

Prior research on exposure fairness in the context of recommender systems has focused mostly on disparities in the exposure of individual or groups of items to individual users of the system. The problem of how individual or groups of items…

Information Retrieval · Computer Science 2022-05-03 Haolun Wu , Bhaskar Mitra , Chen Ma , Fernando Diaz , Xue Liu

Information is transmitted through websites, and immediate reactions to various kinds of information are required. Hence, efforts by users to select information themselves have increased, which is fueling further improvements in…

Information Retrieval · Computer Science 2018-07-18 Atom Sonoda , Fujio Toriumi , Hiroto Nakajima , Miyabi Gouji

The increasing reliance on digital platforms shapes how individuals understand the world, as recommendation systems direct users toward content "similar" to their existing preferences. While this process simplifies information retrieval,…

Computational Engineering, Finance, and Science · Computer Science 2024-12-17 Minhyeok Lee

Music listening in today's digital spaces is highly characterized by the availability of huge music catalogues, accessible by people all over the world. In this scenario, recommender systems are designed to guide listeners in finding tracks…

Human-Computer Interaction · Computer Science 2022-01-26 Lorenzo Porcaro , Emilia Gómez , Carlos Castillo

Political polarization appears to be on the rise, as measured by voting behavior, general affect towards opposing partisans and their parties, and contents posted and consumed online. Research over the years has focused on the role of the…

Social and Information Networks · Computer Science 2021-04-15 Kiran Garimella , Tim Smith , Rebecca Weiss , Robert West

Recommender systems often struggle with over-specialization, which severely limits users' exposure to diverse content and creates filter bubbles that reduce serendipitous discovery. To address this fundamental limitation, this paper…

Information Retrieval · Computer Science 2026-05-27 Edoardo Bianchi

Recommendation algorithms play a pivotal role in shaping our media choices, which makes it crucial to comprehend their long-term impact on user behavior. These algorithms are often linked to two critical outcomes: homogenization, wherein…

Computers and Society · Computer Science 2024-03-11 Md Sanzeed Anwar , Grant Schoenebeck , Paramveer S. Dhillon

Individuals' access to information in a social network depends on its distributed and where in the network individuals position themselves. However, individuals have limited capacity to manage their social connections and process…

Social and Information Networks · Computer Science 2015-04-09 Jeon-Hyung Kang , Kristina Lerman

Personalization is pervasive in the online space as, when combined with learning, it leads to higher efficiency and revenue by allowing the most relevant content to be served to each user. However, recent studies suggest that such…

Computers and Society · Computer Science 2017-07-10 L. Elisa Celis , Nisheeth K. Vishnoi

Social media platforms moderate content for each user by incorporating the outputs of both platform-wide content moderation systems and, in some cases, user-configured personal moderation preferences. However, it is unclear (1) how end…

Human-Computer Interaction · Computer Science 2025-06-13 Shagun Jhaver , Alice Qian Zhang , Quanze Chen , Nikhila Natarajan , Ruotong Wang , Amy Zhang

In consumer search, there is a set of items. An agent has a prior over her value for each item and can pay a cost to learn the instantiation of her value. After exploring a subset of items, the agent chooses one and obtains a payoff equal…

Computer Science and Game Theory · Computer Science 2019-05-15 Nicole Immorlica , Jieming Mao , Christos Tzamos

Personalized recommendation systems shape much of user choice online, yet their targeted nature makes separating out the value of recommendation and the underlying goods challenging. We build a discrete choice model that embeds…

General Economics · Economics 2026-03-30 Kevin Zielnicki , Guy Aridor , Aurélien Bibaut , Allen Tran , Winston Chou , Nathan Kallus

Recommender systems underpin many of the personalized services in the online information & social media ecosystem. However, the assumptions in the research on content recommendations in domains like search, video, and music are often…

Social and Information Networks · Computer Science 2024-09-23 Nathan Bartley , Kristina Lerman

The social brain hypothesis fixes to 150 the number of social relationships we are able to maintain. Similar cognitive constraints emerge in several aspects of our daily life, from our mobility up to the way we communicate, and might even…

Social and Information Networks · Computer Science 2020-10-06 Matteo Cinelli , Emanuele Brugnoli , Ana Lucia Schmidt , Fabiana Zollo , Walter Quattrociocchi , Antonio Scala
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