Do not blame it on the algorithm: an empirical assessment of multiple recommender systems and their impact on content diversity

J Möller, D Trilling, N Helberger… - Digital media, political …, 2020 - taylorfrancis.com
In the debate about filter bubbles caused by algorithmic news recommendation, the
conceptualization of the two core concepts in this debate, diversity and algorithms, has …

Novelty and diversity in recommender systems

P Castells, N Hurley, S Vargas - Recommender systems handbook, 2021 - Springer
Novelty and diversity have been identified, along with accuracy, as prominent properties of
useful recommendations. Considerable progress has been made in the field in terms of the …

How motivational feedback increases user's benefits and continued use: A study on gamification, quantified-self and social networking

L Hassan, A Dias, J Hamari - International Journal of Information …, 2019 - Elsevier
With the increasing provenance of hedonic and social information systems, systems are
observed to employ other forms of feedback and design than purely informational in order to …

Exploring author gender in book rating and recommendation

MD Ekstrand, M Tian, MRI Kazi… - Proceedings of the 12th …, 2018 - dl.acm.org
Collaborative filtering algorithms find useful patterns in rating and consumption data and
exploit these patterns to guide users to good items. Many of the patterns in rating datasets …

User perception of differences in recommender algorithms

MD Ekstrand, FM Harper, MC Willemsen… - Proceedings of the 8th …, 2014 - dl.acm.org
Recent developments in user evaluation of recommender systems have brought forth
powerful new tools for understanding what makes recommendations effective and useful …

Gamification, quantified-self or social networking? Matching users' goals with motivational technology

J Hamari, L Hassan, A Dias - User Modeling and User-Adapted Interaction, 2018 - Springer
Abstract Systems and services we employ in our daily life have increasingly been
augmented with motivational designs which fall under the classes of (1) gamification,(2) …

Psychology-informed recommender systems

E Lex, D Kowald, P Seitlinger, TNT Tran… - … and trends® in …, 2021 - nowpublishers.com
Personalized recommender systems have become indispensable in today's online world.
Most of today's recommendation algorithms are data-driven and based on behavioral data …

Evaluating conversational recommender systems: A landscape of research

D Jannach - Artificial Intelligence Review, 2023 - Springer
Conversational recommender systems aim to interactively support online users in their
information search and decision-making processes in an intuitive way. With the latest …

Artificial intelligence ecosystems for marketing communications

E Malthouse, J Copulsky - International Journal of Advertising, 2023 - Taylor & Francis
The goal of this article is to help advertising scholars, students and practitioners understand
and anticipate the effects of artificial intelligence (AI) and machine learning (ML) on …

Nudging towards health? examining the merits of nutrition labels and personalization in a recipe recommender system

A El Majjodi, AD Starke, C Trattner - … of the 30th ACM conference on user …, 2022 - dl.acm.org
Food recommender systems show personalized recipes to users based on content liked
previously. Despite their potential, often recommended (popular) recipes in previous studies …