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In video recommendation, a critical component that determines the system's recommendation accuracy is the watch-time prediction module, since how long a user watches a video directly reflects personalized preferences. One of the key…

A new statistical based model approach to characterize a user's behavior in an Internet access link is presented. The real patterns of Internet traffic in a heterogeneous Campus Network are studied. We find three clearly different patterns…

The digital traces we leave behind when engaging with the modern world offer an interesting lens through which we study behavioral patterns as expression of gender. Although gender differentiation has been observed in a number of settings,…

Predicting human displacements is crucial for addressing various societal challenges, including urban design, traffic congestion, epidemic management, and migration dynamics. While predictive models like deep learning and Markov models…

Loneliness has reached epidemic proportions globally, posing serious risks to mental and physical health. As social media platforms increasingly mediate social interaction, understanding their relationship with loneliness has become urgent.…

Recommender systems rely heavily on user feedback to learn effective user and item representations. Despite their widespread adoption, limited attention has been given to the uncertainty inherent in the feedback used to train these systems.…

One vision of future wireless networks is that they will be deeply integrated and embedded in our lives and will involve the use of personalized mobile devices. User behavior in such networks is bound to affect the network performance. It…

More and more people use the Internet to work on duties of their daily work routine. To find the right information online, Web search engines are the tools of their choice. Apart from finding facts, people use Web search engines to also…

The ability to predict social interactions between people has profound applications including targeted marketing and prediction of information diffusion and disease propagation. Previous work has shown that the location of an individual at…

This paper aims to stir debate about a disconcerting privacy issue on web browsing that could easily emerge because of unethical practices and uncontrolled use of technology. We demonstrate how straightforward is to capture behavioral data…

The growth of world-wide-web (WWW) spreads its wings from an intangible quantities of web-pages to a gigantic hub of web information which gradually increases the complexity of crawling process in a search engine. A search engine handles a…

The daily activities performed by a disabled or elderly person can be monitored by a smart environment, and the acquired data can be used to learn a predictive model of user behavior. To speed up the learning, several researchers designed…

Predictive human models often need to adapt their parameters online from human data. This raises previously ignored safety-related questions for robots relying on these models such as what the model could learn online and how quickly could…

The study of human interactions is of central importance for understanding the behavior of individuals, groups and societies. Here, we observe the formation and evolution of networks by monitoring the addition of all new links and we…

Human routines structure daily life, yet remain challenging for computational systems to understand. This paper presents the first systematic review of routine computing, a previously implicit but increasingly recognized field that focuses…

In human-in-the-loop machine learning, the user provides information beyond that in the training data. Many algorithms and user interfaces have been designed to optimize and facilitate this human--machine interaction; however, fewer studies…

Wearable devices, or "wearables," bring great benefits but also potential risks that could expose users' activities with- out their awareness or consent. In this paper, we report findings from the first large-scale survey conducted to…

Predicting when an individual will adopt a new behavior is an important problem in application domains such as marketing and public health. This paper examines the perfor- mance of a wide variety of social network based measurements…

Mobility and network traffic have been traditionally studied separately. Their interaction is vital for generations of future mobile services and effective caching, but has not been studied in depth with real-world big data. In this paper,…

User response to contributed content in online social media depends on many factors. These include how the site lays out new content, how frequently the user visits the site, how many friends the user follows, how active these friends are,…