helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
Compared with traditional ranked list interfaces, which more effectively adapts to changing user preferences: carousel interfaces?Direction: Recommendation, Personalization, and Exploration
Recommendation Algorithms, Ranking, and Social Recommendation
Stats are based on currently indexed question data; missing sources remain visible.
92
items
24
sources
2025
latest
All questions
92 items
helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
Can carousel interfaces significantly reduce users' navigation costs?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
Can carousel interfaces improve users' content exploration efficiency and decision comfort?lightbulbPractical problemRecommendation Algorithms, Ranking, and Social Recommendation
Users struggle to efficiently explore and discover content in content-rich recommendation systems.helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How can multi-objective recommendation ranking systems be designed and evaluated to optimize multiple goals while meeting the needs of different stakeholders?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How can cross-functional team collaboration efficiency improve the design and evaluation of multi-objective rankers?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
Can comprehensive information analysis tools help users balance trade-offs among different objectives under design changes?lightbulbPractical problemRecommendation Algorithms, Ranking, and Social Recommendation
Multi-objective optimization design in recommender systems is complex, and team collaboration efficiency is low.helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
In game social recommendation, how can a dynamic balance be achieved between similarity and diversity?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How can human-AI collaboration techniques improve recommender system transparency and user controllability?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How can fine-grained preference modeling and active learning mechanisms improve game social recommendation effectiveness?lightbulbPractical problemRecommendation Algorithms, Ranking, and Social Recommendation
Players in multiplayer online games struggle to find social recommendations that balance similarity and diversity.helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How can multi-agent interaction systems (e.g., CML) enhance users' multi-perspective understanding of film narrative and themes?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How does cross-universe character interaction affect film appreciation experience?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
Can users achieve personalized film discussion experiences by freely choosing agent combinations?lightbulbPractical problemRecommendation Algorithms, Ranking, and Social Recommendation
Film fans lack deep, multi-perspective support when discussing movies online.helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
What are the limitations of traditional recommendation-style AI in complex open-ended decision tasks?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How does the ExtendAI mode better support users' decision logic than traditional RecommendAI approaches?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
What role do LLMs play in augmenting users' reasoning processes?lightbulbPractical problemRecommendation Algorithms, Ranking, and Social Recommendation
When handling complex problems, users struggle to integrate AI suggestions into decisions and may become overly dependent.helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How do location-based recommendation systems and digital surveillance affect user behavior, emotion, and autonomy?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
Can high-fidelity design fiction (high-fidelity films) effectively promote expert reflection on technology ethics?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
What potential do high-fidelity films have in guiding public participation in discussions of technological futures?lightbulbPractical problemRecommendation Algorithms, Ranking, and Social Recommendation
Everyday location-based recommendation and surveillance technologies infringe on user privacy and autonomy.helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How do users influence personalized recommender content generation through explicit and implicit behavioral feedback?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
Can existing explicit-implicit feedback models accurately capture user intent and behavioral strategies?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
What purposes and goals do users have when using explicit versus implicit feedback?lightbulbPractical problemRecommendation Algorithms, Ranking, and Social Recommendation
Personalized recommendations lack diversity, potentially limiting UX.helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How do voice assistant tone (positive, neutral, negative) affect persuasiveness and users' purchase decisions?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How do voice assistant age and gender characteristics affect users' perceptions of credibility and expertise?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
What are users' preferences for personalized voice assistant voice settings?lightbulbPractical problemRecommendation Algorithms, Ranking, and Social Recommendation
Users have low trust in voice assistants for complex tasks, such as online shopping recommendations.helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
Can group recommender systems (GRSs) serve as media for social interaction, promoting indirect communication among users?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How does Spotify Blend function in users' everyday social contexts and affect user experience?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
What roles do recommendation algorithm opacity and visibility of user behavior play in enhancing social interaction?lightbulbPractical problemRecommendation Algorithms, Ranking, and Social Recommendation
Users struggle to naturally strengthen everyday social connections through technology.helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How do adolescents perceive the relationship between personalized recommended content and their self-concept?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How do the accuracy and inaccuracy of personalized recommended content affect adolescents' emotional experience and identity?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How much do adolescents trust data doubles reflecting their identity?lightbulbPractical problemRecommendation Algorithms, Ranking, and Social Recommendation
Personalized content recommendations for adolescents may be overly precise, hindering diversity and self-reflection.helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How can 'teachable feeds' in social media better capture users' complex content preferences?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
In user–recommender algorithm interaction, which design principles enhance user autonomy and trust?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How can users adjust social media feed content recommendations through multimodal interaction (e.g., buttons, natural language)?lightbulbPractical problemRecommendation Algorithms, Ranking, and Social Recommendation
Users struggle to effectively control feed content shaped by social media recommendation algorithms.helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How can voice assistants enable proactive time management and improve user experience?CUI '23Voicing Suggestions and Enabling Reflection: Results of an Expert Discussion on Proactive Assistants for Time Management
helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
In time management, how can system transparency (data transparency) be balanced with personalized recommendations?CUI '23Voicing Suggestions and Enabling Reflection: Results of an Expert Discussion on Proactive Assistants for Time Management
helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
Can voice-controlled assistants optimize interaction effectiveness in multi-party collaboration scenarios through user modeling?CUI '23Voicing Suggestions and Enabling Reflection: Results of an Expert Discussion on Proactive Assistants for Time Management
lightbulbPractical problemRecommendation Algorithms, Ranking, and Social Recommendation
Users perceive existing voice assistants as insufficiently proactive and unable to efficiently manage busy schedules.CUI '23Voicing Suggestions and Enabling Reflection: Results of an Expert Discussion on Proactive Assistants for Time Management
helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How do cultural values affect users' friend network structure on non-open social networks (e.g., Snapchat)?helpResearch questionRecommendation Algorithms, Ranking, and Social Recommendation
How do cultural values moderate the effect of relationship strength on content consumption behavior?Related papers
IUI 2025
Under the Hood of Carousels: Investigating User Engagement and Navigation Effort in Multi-list Recommender Systems
Behnam Rahdari, Peter Brusilovsky
IUI 2025
Orbit: A Framework for Designing and Evaluating Multi-objective Rankers
Chenyang Yang, Tesi Xiao, Michael Shavlovsky
IUI 2025
Prefer2SD: A Human-in-the-Loop Approach to Balancing Similarity and Diversity in In-Game Friend Recommendations
Xiyuan Wang, Ziang Li, Sizhe Chen
CHI 2025
Cinema Multiverse Lounge: Enhancing Film Appreciation via Multi-Agent Conversations
Kyusik Kim, Jeongwoo Ryu, Dongseok Heo
CHI 2025
AI, Help Me Think—but for Myself: Assisting People in Complex Decision-Making by Providing Different Kinds of Cognitive Support
Leon Reicherts, Zelun Tony Zhang, Elisabeth von Oswald
CHI 2025
Exploring the use of Speculative Concept Films for Co-Speculation around Data Ethics
Wyatt Olson, James Pierce
CHI 2025
Beyond Explicit and Implicit: How Users Provide Feedback to Shape Personalized Recommendation Content
Wenqi Li, Jui-Ching Kuo, Manyu Sheng
CUI 2024
The Impact of Perceived Tone, Age, and Gender on Voice Assistant Persuasiveness in the Context of Product Recommendations
Sabid Bin Habib Pias, Ran Huang, Donald S. Williamson
CHI 2024
Investigating the Potential of Group Recommendation Systems As a Medium of Social Interactions: A Case of Spotify Blend Experiences between Two Users
Daehyun Kwak, Soobin Park, Inha Cha
CHI 2024
For Me or Not for Me? The Ease With Which Teens Navigate Accurate and Inaccurate Personalized Social Media Content
Nora McDonald, John S. Seberger, Afsaneh Razi
CHI 2024
Mapping the Design Space of Teachable Social Media Feed Experiences
K. J. Kevin Feng, Xander Koo, Lawrence Tan
CHI 2023
Cultural Differences in Friendship Network Behaviors: A Snapchat Case Study
Agrima Seth, Jiyin Cao, Xiaolin Shi