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Collaborative Filtering (CF) models, despite their great success, suffer from severe performance drops due to popularity distribution shifts, where these changes are ubiquitous and inevitable in real-world scenarios. Unfortunately, most…

Information Retrieval · Computer Science 2023-05-19 An Zhang , Jingnan Zheng , Xiang Wang , Yancheng Yuan , Tat-Seng Chua

Learning from the crowd has become increasingly popular in the Web and social media. There is a wide variety of crowdlearning sites in which, on the one hand, users learn from the knowledge that other users contribute to the site, and, on…

Social and Information Networks · Computer Science 2016-12-16 Utkarsh Upadhyay , Isabel Valera , Manuel Gomez-Rodriguez

Searching for and making decisions about information is becoming increasingly difficult as the amount of information and number of choices increases. Recommendation systems help users find items of interest of a particular type, such as…

Information Retrieval · Computer Science 2011-07-04 M. H. Goker , P. Langley , C. A. Thompson

The voter model and the Axelrod model are two of the main stochastic processes that describe the spread of opinions on networks. The former includes social influence, the tendency of individuals to become more similar when they interact,…

Probability · Mathematics 2010-12-30 Nicolas Lanchier

Commons-based peer production does seem to rest upon a paradox. Although users produce all contents, at the same time participation is commonly on a voluntary basis, and largely incentivized by achievement of project's goals. This means…

Physics and Society · Physics 2011-10-11 Giovanni Luca Ciampaglia

In order to truly understand how social media might shape online discourses or contribute to societal polarization, we need refined models of platform choice, that is: models that help us understand why users prefer one social media…

Adaptation and Self-Organizing Systems · Physics 2024-11-08 Sven Banisch , Dennis Jacob , Tom Willaert , Eckehard Olbrich

Providing explanations for recommended items allows users to refine the recommendations by critiquing parts of the explanations. As a result of revisiting critiquing from the perspective of multimodal generative models, recent work has…

Information Retrieval · Computer Science 2022-04-06 Diego Antognini , Boi Faltings

To promote constructive discussion of controversial topics online, we propose automatic reframing of disagreeing responses to signal receptiveness to a preceding comment. Drawing on research from psychology, communications, and linguistics,…

Computation and Language · Computer Science 2024-10-08 Gauri Kambhatla , Matthew Lease , Ashwin Rajadesingan

We investigate opinion dynamics in multi-agent networks when a bias toward one of two possible opinions exists; for example, reflecting a status quo vs a superior alternative. Starting with all agents sharing an initial opinion representing…

Multiagent Systems · Computer Science 2021-03-09 Aris Anagnostopoulos , Luca Becchetti , Emilio Cruciani , Francesco Pasquale , Sara Rizzo

Conversational information access is an emerging research area. Currently, human evaluation is used for end-to-end system evaluation, which is both very time and resource intensive at scale, and thus becomes a bottleneck of progress. As an…

Information Retrieval · Computer Science 2020-06-17 Shuo Zhang , Krisztian Balog

An ability to predict the popularity dynamics of individual items within a complex evolving system has important implications in an array of areas. Here we propose a generative probabilistic framework using a reinforced Poisson process to…

Social and Information Networks · Computer Science 2014-01-07 Hua-Wei Shen , Dashun Wang , Chaoming Song , Albert-László Barabási

Sentiment analysis has attracted increasing attention in e-commerce. The sentiment polarities underlying user reviews are of great value for business intelligence. Aspect category sentiment analysis (ACSA) and review rating prediction (RP)…

Computation and Language · Computer Science 2021-05-04 Jiahao Bu , Lei Ren , Shuang Zheng , Yang Yang , Jingang Wang , Fuzheng Zhang , Wei Wu

Human activities increasingly take place in online environments, providing novel opportunities for relating individual behaviours to population-level outcomes. In this paper, we introduce a simple generative model for the collective…

Physics and Society · Physics 2014-07-24 James P. Gleeson , Davide Cellai , Jukka-Pekka Onnela , Mason A. Porter , Felix Reed-Tsochas

Just as user preferences change with time, item reviews also reflect those same preference changes. In a nutshell, if one is to sequentially incorporate review content knowledge into recommender systems, one is naturally led to dynamical…

Information Retrieval · Computer Science 2022-03-23 Kostadin Cvejoski , Ramses J. Sanchez , Christian Bauckhage , Cesar Ojeda

In epistemic community, people are said to be selected on their knowledge contribution to the project (articles, codes, etc.) However, the socialization process is an important factor for inclusion, sustainability as a contributor, and…

Social and Information Networks · Computer Science 2015-01-08 Romain Picot-Clémente , Cécile Bothorel , Nicolas Jullien

Despite the prevalence of voting systems in the real world there is no consensus among researchers of how people vote strategically, even in simple voting settings. This paper addresses this gap by comparing different approaches that have…

Computer Science and Game Theory · Computer Science 2019-09-24 Roy Fairstein , Adam Lauz , Kobi Gal , Reshef Meir

Public opinion is subject to peer interaction via social networks and external pressure from the media, advertising, and other actors. In this paper, we study the interaction between external and peer influence on the stochastic opinion…

Physics and Society · Physics 2024-07-31 Niels Van Santen , Jan Ryckebusch , Luis E. C. Rocha

Recommender systems learn from historical users' feedback that is often non-uniformly distributed across items. As a consequence, these systems may end up suggesting popular items more than niche items progressively, even when the latter…

Information Retrieval · Computer Science 2020-10-06 Ludovico Boratto , Gianni Fenu , Mirko Marras

TurboTax AnswerXchange is a social Q&A system supporting users working on federal and state tax returns. Using 2015 data, we demonstrate that content popularity (or number of views per AnswerXchange question) can be predicted with…

Information Retrieval · Computer Science 2016-01-19 Igor A. Podgorny

Iterative voting is a natural model of repeated strategic decision-making in social choice theory when agents have the opportunity to update their votes prior to finalizing the group decision. Prior work has analyzed the efficacy of…

Computer Science and Game Theory · Computer Science 2025-06-12 Joshua Kavner , Lirong Xia