Related papers: What's in a Session: Tracking Individual Behavior …
Browser fingerprinting consists in collecting attributes from a web browser to build a browser fingerprint. In this work, we assess the adequacy of browser fingerprints as an authentication factor, on a dataset of 4,145,408 fingerprints…
We introduce a semantic identification attack, in which an adversary uses semantic signals about the pages visited in one browsing session to identify other browsing sessions launched by the same user. Current user fingerprinting methods…
Interactions between users in cyberspace may lead to phenomena different from those observed in common social networks. Here we analyse large data sets about users and Blogs which they write and comment, mapped onto a bipartite graph. In…
We introduce a formalism based on a continuous time approximation, to study the characteristics of Page Rank random walks. We find that the diffusion of the occupancy probability has a dynamics that exponentially "forgets" the initial…
Compared to the well-studied topic of human mobility in real geographic space, very few studies focus on human mobility in virtual space, such as interests, knowledge, ideas, and so forth. However, it relates to the issues of management of…
The Internet of Behavior is a research theme that aims to analyze human behavior data on the Internet from the perspective of behavioral psychology, obtain insights about human behavior, and better understand the intention behind the…
This paper investigates whether computer usage profiles comprised of process-, network-, mouse-, and keystroke-related events are unique and consistent over time in a naturalistic setting, discussing challenges and opportunities of using…
Most popular web browsers include "reader modes" that improve the user experience by removing un-useful page elements. Reader modes reformat the page to hide elements that are not related to the page's main content. Such page elements…
Most of the existing recommender systems assume that user's visiting history can be constantly recorded. However, in recent online services, the user identification may be usually unknown and only limited online user behaviors can be used.…
A powerful means to help users discover new content in the overwhelming amount of information available today is sharing in online communities such as social networks or crowdsourced platforms. This means comes short in the case of what we…
Browsers and their users can be tracked even in the absence of a persistent IP address or cookie. Unique and hence identifying pieces of information, making up what is known as a fingerprint, can be collected from browsers by a visited…
Being able to automatically and quickly understand the user context during a session is a main issue for recommender systems. As a first step toward achieving that goal, we propose a model that observes in real time the diversity brought by…
Modern society depends on the flow of information over online social networks, and users of popular platforms generate significant behavioral data about themselves and their social ties. However, it remains unclear what fundamental limits…
In recent years, social virtual reality (VR), sometimes described as the "metaverse," has become widely available. With its potential comes risks, including risks to privacy. To understand these risks, we study the identifiability of…
The web page usage mining plays a vital role in enriching the page's content and structure based on the feedbacks received from the user's interactions with the page. This paper proposes a model for micro-managing the tracking activities by…
Individual personalities significantly influence our perceptions, decisions, and social interactions, which is particularly crucial for gaining insights into human behavior patterns in online social network analysis. Many psychological…
The paper proposes an approach to modeling users of large Web sites based on combining different data sources: access logs and content of the accessed pages are combined with semantic information about the Web pages, the users and the…
Session-based Recommendation (SR) aims to predict the next item for recommendation based on previously recorded sessions of user interaction. The majority of existing approaches to SR focus on modeling the transition patterns of items. In…
Broadcasts and timelines are the primary mechanism of information exchange in online social platforms today. Services like Facebook, Twitter and Instagram have enabled ordinary people to reach large audiences spanning cultures and…
Capturing both the structural and temporal aspects of interactions is crucial for many real world datasets like contact between individuals. Using the link stream formalism to capture the dynamic of the systems, we tackle the issue of…