RecGaze Dataset - Public Version

This is the public RecGaze dataset from the paper: RecGaze: The First Eye Tracking and User Interaction Dataset for Carousel Interfaces

Link to open-acess paper: SIGIR 2025, Arxiv

Follow-up eye tracking analysis of user browsing behavior: IUI 2026

Follow-up click modeling paper on observed examination position-based click models for carousels: Arxiv

The dataset is also available in a simplified click dataset version suitable for click modeling that can be openly downloaded: RecGaze Click Feedback Dataset

Please cite the following: 

@inproceedings{10.1145/3726302.3730301,author = {de Leon-Martinez, Santiago and Kang, Jingwei and Moro, Robert and de Rijke, Maarten and Kveton, Branislav and Oosterhuis, Harrie and Bielikova, Maria},title = {RecGaze: The First Eye Tracking and User Interaction Dataset for Carousel Interfaces},year = {2025},isbn = {9798400715921},publisher = {Association for Computing Machinery},address = {New York, NY, USA},url = {https://doi.org/10.1145/3726302.3730301},doi = {10.1145/3726302.3730301},booktitle = {Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval},pages = {3702–3711},numpages = {10},keywords = {browsing behavior, carousel interfaces, eye tracking},location = {Padua, Italy},series = {SIGIR '25}}

@inproceedings{10.1145/3742413.3789166,author = {de Leon-Martinez, Santiago and Moro, Robert and Kveton, Branislav and Bielikova, Maria},title = {Riding the Carousel: The First Extensive Eye Tracking Analysis of Browsing Behavior in Carousel Recommenders},year = {2026},isbn = {9798400719844},publisher = {Association for Computing Machinery},address = {New York, NY, USA},url = {https://doi.org/10.1145/3742413.3789166},doi = {10.1145/3742413.3789166},booktitle = {Proceedings of the 31st International Conference on Intelligent User Interfaces},pages = {2120–2130},numpages = {11},keywords = {Carousel interfaces, Multi-list recommendations, Browsing behavior, Eye tracking},location = {},series = {IUI '26}}

Dataset Description

The RecGaze dataset is the first comprehensive feedback dataset on carousels that includes eye tracking results, clicks, cursor movements, and selection explanations. The dataset comprises of interactions from 3  movie selection tasks with 40 different carousel interfaces per user. In total, 87 users and 3,477 interactions are logged.

Public Dataset download contains:

Summary Feedback Dataframe (summary_feedback.csv) - All the feedback (fixations, clicks, cursor movements) data gathered during the movie selection screens

Click Feedback Dataframe (click_feedback.csv) -  Summary dataframe, primarily for click modeling and other Recommender usages, that only contains the last movie selection click per user, screen pair.

Item Features Dataframe (item_features.csv) - Contains all the information for the movies used to create the carousel screens along with extra data that was not used for the study. 

User Features Dataframe (user_features.csv) - Contains all the information gathered from the users during the pre-survey, post-survey, and post-selection screens (selection explanations). 

A more detailed description of all the files and their contents (along with supplementary material) can be found in the GitHub.

Non-public Version

The non-public version additionally contains the following (for a more in-depth explanation and examples see paper, Table 2 ):

User Features

Age 

Gender

Answer to most helpful carousel topic/explanation question

Summary Feedback Dataframe

x,y pixel postions for fixation, cursor, clicks

Raw Gaze data 

Other

Screen recordings of every movie selection task for all users and screens

For the non-public version of the dataset, request access through this link