Measuring Online Behavior Change with Observational Studies: a Review

October 30, 2023 ยท The Cartographer ยท ๐Ÿ› ACM Computing Surveys

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: Measuring Online Behavior Change with Observational Studies: a Review"

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Authors Arianna Pera, Gianmarco de Francisci Morales, Luca Maria Aiello arXiv ID 2310.19951 Category cs.CY: Computers & Society Cross-listed cs.SI, physics.soc-ph Citations 0 Venue ACM Computing Surveys Last Checked 4 days ago
Abstract
Exploring online behavior change is imperative for societal progress in the context of 21st-century challenges. We analyze 148 articles (2000-2023) focusing on behavior change in the digital space and build a map that categorizes behaviors, behavior change detection methodologies, platforms of reference, and theoretical frameworks that characterize the analysis of online behavior change. Our findings reveal a focus on sentiment shifts, an emphasis on API-restricted platforms, and limited integration of theory. We call for methodologies able to capture a wider range of behavior types, diverse data sources, and stronger theory-practice alignment in the study of online behavior and its change.
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