ArticleScientific data2025
A dataset of interactions and emotions for website user experience evaluation.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A dataset of interactions and emotions for website user experience evaluation.Scientific data · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
This data descriptor introduces a dataset designed for affective computing applications in the context of human-computer interaction, with a particular focus on user experience (UX) and website interactions. The dataset comprises interaction logs, including mouse movements and key presses, collected over a period of 30 days from various websites. Each recorded interaction is paired with corresponding emotional data, which is encoded according to Ekman's emotion model, allowing for a nuanced analysis of emotional responses. This dataset is particularly valuable for examining how emotions influence user behaviour, and vice versa, also across different types of websites. Its primary aim is to facilitate the development of Artificial Intelligence (AI) systems capable of detecting user emotions solely based on user interaction data. Such systems have potential applications in improving UX design, personalizing web content, and enhancing the overall UX by adapting to emotional states without requiring explicit input from users.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.