VIKI: Systematic Cross-Platform Profile Inference of Tech Users

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 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.

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Publication Details

Published
2025-05-19
DOI
https://doi.org/10.1145/3717867.3717890
Citations
1
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
4.20

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article

VIKI: Systematic Cross-Platform Profile Inference of Tech Users

Ben Treves, Michalis Faloutsos, Emiliano De Cristofaro, Yue Dong
1 citations
Digital Marketing and Social Media
4.20
article

VIKI: Systematic Cross-Platform Profile Inference of Tech Users

Ben Treves, Michalis Faloutsos, Emiliano De Cristofaro, Yue Dong
article en
1 citations

Abstract

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 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.

University of California, Riverside (US)
National Science Foundation
Openalex Percentile: Top 8%
Digital Marketing and Social Media
4.20
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