Year: 2024
Type: conference-paper
Abstract: In this paper, we present the Informfully Dataset with Enhanced Attributes (IDEA) for news article recommendations. The dataset consists of an open-source collection of user profiles, news articles with a high topic and outlet diversity, item recommendations, and rich user-item interactions from a field study on behavioral changes in news consumption. The records include both quantitative data from real-time session tracking as well as self-reported data from user surveys on satisfaction with news, knowledge acquisition, and personal background information. This paper outlines the data collection procedure and potential use cases of the dataset for designing normative recommender systems. It provides the documentation of all data collections together with insights into the data quality.
DOI: 10.5167/uzh-262715
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6910979927
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