VIKI: Systematic Cross-Platform Profile Inference of Online Users

Fuente: arXiv
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Hauptverfasser: Treves, Ben, De Cristofaro, Emiliano, Dong, Yue, Faloutsos, Michalis
Format: Preprint
Veröffentlicht: 2025
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author Treves, Ben
De Cristofaro, Emiliano
Dong, Yue
Faloutsos, Michalis
author_facet Treves, Ben
De Cristofaro, Emiliano
Dong, Yue
Faloutsos, Michalis
contents What can we learn about online users by comparing their profiles across different platforms? We use the term profile to represent displayed personality traits, interests, and behavioral patterns (e.g., offensiveness). We also use the term {\it displayed personas} to refer to the personas that users manifest on a platform. Though individuals have a single real persona, it is not difficult to imagine that people can behave differently in different ``contexts'' as it happens in real life (e.g., behavior in office, bar, football game). The vast majority of previous studies have focused on profiling users on a single platform. Here, we propose VIKI, a systematic methodology for extracting and integrating the displayed personas of users across different social platforms. First, we extract multiple types of information, including displayed personality traits, interests, and offensiveness. Second, we evaluate, combine, and introduce methods to summarize and visualize cross-platform profiles. Finally, we evaluate VIKI on a dataset that spans three platforms -- GitHub, LinkedIn, and X. Our experiments show that displayed personas change significantly across platforms, with over 78% of users exhibiting a significant change. For instance, we find that neuroticism exhibits the largest absolute change. We also identify significant correlations between offensive behavior and displayed personality traits. Overall, we consider VIKI as an essential building block for systematic and nuanced profiling of users across platforms.
format Preprint
id arxiv_https___arxiv_org_abs_2503_14772
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle VIKI: Systematic Cross-Platform Profile Inference of Online Users
Treves, Ben
De Cristofaro, Emiliano
Dong, Yue
Faloutsos, Michalis
Social and Information Networks
What can we learn about online users by comparing their profiles across different platforms? We use the term profile to represent displayed personality traits, interests, and behavioral patterns (e.g., offensiveness). We also use the term {\it displayed personas} to refer to the personas that users manifest on a platform. Though individuals have a single real persona, it is not difficult to imagine that people can behave differently in different ``contexts'' as it happens in real life (e.g., behavior in office, bar, football game). The vast majority of previous studies have focused on profiling users on a single platform. Here, we propose VIKI, a systematic methodology for extracting and integrating the displayed personas of users across different social platforms. First, we extract multiple types of information, including displayed personality traits, interests, and offensiveness. Second, we evaluate, combine, and introduce methods to summarize and visualize cross-platform profiles. Finally, we evaluate VIKI on a dataset that spans three platforms -- GitHub, LinkedIn, and X. Our experiments show that displayed personas change significantly across platforms, with over 78% of users exhibiting a significant change. For instance, we find that neuroticism exhibits the largest absolute change. We also identify significant correlations between offensive behavior and displayed personality traits. Overall, we consider VIKI as an essential building block for systematic and nuanced profiling of users across platforms.
title VIKI: Systematic Cross-Platform Profile Inference of Online Users
topic Social and Information Networks
url https://arxiv.org/abs/2503.14772