Erez Shmueli

Erez Shmueli
Tel Aviv University | TAU · Department of Industrial Engineering

About

83
Publications
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Introduction

Publications

Publications (83)
Article
Full-text available
Cities have been extensively studied as complex adaptive systems over the last 50 years. Recently, several empirical studies and emerging theory provided support for the fact that many different urban indicators follow general consistent statistical patterns across countries, cultures and times. In particular, total personal income, measures of inn...
Article
Full-text available
More than 12 billion COVID-19 vaccination shots have been administered as of August 2022, but information from active surveillance about vaccine safety is limited. Surveillance is generally based on self-reporting, making the monitoring process subjective. We study participants in Israel who received their second or third Pfizer BioNTech COVID-19 v...
Article
Full-text available
Numerous studies over the past decades established that real-world networks typically follow preferential attachment and detachment principles. Subsequently, this implies that degree fluctuations monotonically increase while rising up the ‘degree ladder’, causing high-degree nodes to be prone for attachment of new edges and for detachment of existi...
Article
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Halting the rapid clinical deterioration, marked by arterial hypoxemia, is among the greatest challenges clinicians face when treating COVID-19 patients in hospitals. While it is clear that oxygen measures and treatment procedures describe a patient’s clinical condition at a given time point, the potential predictive strength of the duration and ex...
Preprint
COVID-19 remains a global concern due to vaccine protection waning and the emergence of immune-evasive variants. While the effectiveness of a second booster vaccine dose (i.e., fourth inoculation) is well proven, its safety has yet to be fully understood, and vaccine compliance remains low. We conducted a prospective observational study to compare...
Article
Despite extensive technological advances in recent years, objective and continuous assessment of physiologic measures after vaccination is rarely performed. We conducted a prospective observational study to evaluate short-term self-reported and physiologic reactions to the booster BNT162b2 mRNA (Pfizer-BioNTech, https://www.pfizer.com) vaccine dose...
Article
Full-text available
Background Clinical trial guidelines for assessing the safety of vaccines, are primarily based on self-reported questionnaires. Despite the tremendous technological advances in recent years, objective, continuous assessment of physiological measures post-vaccination is rarely performed. Methods We conducted a prospective observational study during...
Preprint
Full-text available
The performance of machine learning algorithms can be considerably improved when trained over larger datasets. In many domains, such as medicine and finance, larger datasets can be obtained if several parties, each having access to limited amounts of data, collaborate and share their data. However, such data sharing introduces significant privacy c...
Preprint
Background: The rapid rise in hospitalizations associated with the Delta-driven COVID-19 resurgence, and the imminent risk of hospital overcrowding, led the Israeli government to initialize a national third (booster) COVID-19 vaccination campaign in early August 2021, offering the BNT162b2 mRNA vaccine to individuals who received their second dose...
Article
In this article, we evaluate, for the first time, the potential of a scheduled seeding strategy for influence maximization in a real-world setting. We first propose methods for analyzing historical data to quantify the infection probability of a node with a given set of properties in a given time and assess the potential of a given seeding strategy...
Article
Current COVID-19 screening efforts mainly rely on reported symptoms and the potential exposure to infected individuals. Here, we developed a machine-learning model for COVID-19 detection that uses four layers of information: (i) sociodemographic characteristics of the individual, (ii) spatio-temporal patterns of the disease, (iii) medical condition...
Article
Researchers across cognitive science, economics, and evolutionary biology have studied the ubiquitous phenomenon of social learning—the use of information about other people's decisions to make your own. Decision-making with the benefit of the accumulated knowledge of a community can result in superior decisions compared to what people can achieve...
Article
An increasing number of decisions regarding the daily lives of human beings are being controlled by artificial intelligence (AI) algorithms. Since they now touch on many aspects of our lives, it is crucial to develop AI algorithms that are not only accurate but also objective and fair. Recent studies have shown that algorithmic decision-making may...
Article
Full-text available
Pertussis is a highly contagious bacterial disease that primarily affects infants. To optimize the pertussis vaccination schedule in Israel and evaluate the cost-effectiveness of alternative strategies that add or remove booster doses, we developed an age-structured model for pertussis transmission. Our model was calibrated using 16 years of data f...
Article
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The unprecedented restrictions imposed due to the COVID-19 pandemic altered our daily habits and severely affected our well-being and physiology. The effect of these changes is yet to be fully understood. Here, we analysed highly detailed data on 169 participants for two to six months, before and during the second COVID-19 lockdown in Israel. We ex...
Article
Full-text available
Vaccination has become one of the most prominent measures for preventing the spread of infectious diseases in modern times. However, mass vaccination of the population may not always be possible due to high costs, severe side effects, or shortage. Therefore, identifying individuals with a high potential of spreading the disease and targeted vaccina...
Preprint
Full-text available
Identifying anomalies in multi-dimensional datasets is an important task in many real-world applications. A special case arises when anomalies are occluded in a small set of attributes, typically referred to as a subspace, and not necessarily over the entire data space. In this paper, we propose a new subspace analysis approach named Agglomerative...
Preprint
Full-text available
Following the birth of Bitcoin and the introduction of the Ethereum ERC20 protocol a decade ago, recent years have witnessed a growing number of cryptographic tokens that are being introduced by researchers, private sector companies and NGOs. The ubiquitous of such Blockchain based cryptocurrencies give birth to a new kind of rising economy, which...
Article
In this paper, we propose a comprehensive analytics framework that can serve as a decision support tool for HR recruiters in real-world settings to improve hiring and placement decisions. The proposed framework follows two main phases: a local prediction scheme for recruitments' success at the level of a single job placement and a mathematical mode...
Article
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Global financial crises have led to the understanding that classical econometric models are limited in comprehending financial markets in extreme conditions, partially since they disregarded complex interactions within the system. Consequently, in recent years research efforts have been directed towards modeling the structure and dynamics of the un...
Article
Recommender systems have become extremely common in recent years and are utilized in a variety of domains such as movies, music, news, products, restaurants, and so on. While a typical recommender system bases its recommendations solely on users’ preference data collected by the system itself, the quality of recommendations can significantly be imp...
Article
Full-text available
Objectives To evaluate the utilisation (overall and by specialty) and the characteristics of second-opinion seekers by insurance type (either health fund or supplementary insurance) in a mixed private-public healthcare. Design An observational study. Setting Secondary care visits provided by a large public health fund and a large supplementary he...
Article
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Societal unrest and similar events are important for societies, but it is often difficult to quantify their effects on individuals, hindering a timely and effective policy-making in emergencies and in particular localized social shocks such as protests. Traditionally, effects are assessed through economic indicators or surveys with relatively low t...
Article
Full-text available
One highly studied topic in the field of social networks is the search for influential nodes that, when seeded(i.e., activated intentionally), may further activate a large portion of the network through a viral contagion process. Indeed, various mathematical models were proposed in the literature to characterize the dynamics of such diffusion proce...
Article
Full-text available
Existing viral-marketing network models commonly assume a preliminary phase in which a marketer actively infects a subset of social network’s users, represented by nodes, followed by a passive viral process, in which nodes infect other nodes without external intervention. However, in real-world commercial scenarios, substantial efforts are often in...
Article
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From the "right to be left alone" to the "right to selective disclosure", privacy has long been thought as the control individuals have over the information they share and reveal about themselves. However, in a world that is more connected than ever, the choices of the people we interact with increasingly affect our privacy. This forces us to rethi...
Article
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Cyber-security systems, which protect networks and computers against cyber attacks, are becoming common due to increasing threats and government regulation. At the same time, the enormous amount of data gathered by cyber-security systems poses a serious threat to the privacy of the people protected by those systems. To ground this threat, we survey...
Article
This paper examines the effectiveness of monetary incentives based on real-time monitoring as means to improve driving behavior of company car drivers. We conducted a 5-months 60-drivers field study with one of the largest public transportation companies in Israel. Driving behavior was measured continuously using In-Vehicle Data Recorders (IVDR) th...
Conference Paper
Full-text available
Identifying anomalies in multi-dimensional datasets is an important task in many real-world applications. A special case arises when anomalies are occluded in a small set of attributes (i.e., subspaces) of the data and not necessarily over the entire data space. In this paper, we propose a new subspace analysis approach named Agglomerative Attribut...
Conference Paper
Recommender systems have become extremely common in recent years, and are utilized in a variety of domains such as movies, music, news, products, restaurants, etc. While a typical recommender system bases its recommendations solely on users' preference data collected by the system itself, the quality of recommendations can significantly be improved...
Article
Nowadays, various static wireless sensor networks (WSN) are deployed in the environment for many purposes: traffic control, pollution monitoring, and so on. The willingness to open these legacy WSNs to the users is emerging, by integrating them to the Internet network as part of the future Internet of Things (IoT), for example, in the context of sm...
Article
Full-text available
Numerus works that study the spread of information in social networks include a spreading mechanism in which a set of nodes is initially infected (i.e. seeded), followed by a viral process, which spontaneously spread the message through the nodes of the network. These models are used to describe the spread of rumors as well as the spread of new pro...
Chapter
Optimizing the use of available resources is one of the key challenges in activities that consist of interactionswith a large number of "target individuals", with the ultimate goal of affecting as many ofthem as possible, such as in marketing, service provision and political campaigns. Typically, the costof interactions is monotonically increasing...
Article
Online signature verification technologies, such as those available in banks and post offices, rely on dedicated digital devices such as tablets or smart pens to capture, analyze and verify signatures. In this paper, we suggest a novel method for online signature verification that relies on the increasingly available hand-worn devices, such as smar...
Conference Paper
We present a novel subspace selection algorithm for anomaly detection. Our method is based on the observation that it is easier to detect anomalies in subspaces comprise of highly correlative attributes. More specifically, it uses the Rokhlin metric [22] to evaluate the smallest information distance in the case of two attributes, and an extension o...
Conference Paper
Full-text available
Many studies in the field of information spread through social networks focus on the detection of influencers. The spread dynamics in most of these studies assumes these influencers are first selected and "infected" with a message, and then this message spreads through the networks by a viral process. The following work presents some difficulties w...
Article
Full-text available
Spam in online social networks (OSNs) is a systemic problem that imposes a threat to these services in terms of undermining their value to advertisers and potential investors, as well as negatively affecting users’ engagement. As spammers continuously keep creating newer accounts and evasive techniques upon being caught, a deeper understanding of t...
Article
Full-text available
Spam in online social networks (OSNs) is a systemic problem that imposes a threat to these services in terms of undermining their value to advertisers and potential investors, as well as negatively affecting users’ engagement. As spammers continuously keep creating newer accounts and evasive techniques upon being caught, a deeper understanding of t...
Conference Paper
Full-text available
One highly studied topic in the field of social networks is the search for influential nodes, that when seeded (i.e. infected intentionally), may infect a large portion of the network through a viral process. However, when it comes to the spread of new products, such viral processes are rather rare. Social influence is indeed an important factor wh...
Article
Full-text available
Collective intelligence is believed to underly the remarkable success of human society. The formation of accurate shared beliefs is one of the key components of human collective intelligence. How are accurate shared beliefs formed in groups of fallible individuals? Answering this question requires a multiscale analysis. We must understand both the...
Chapter
Friendship is a fundamental characteristic of human beings and usually assumed to be reciprocal in nature. Despite this common expectation, in reality, not all friendships by default are reciprocal nor created equal. Here, we show that reciprocated friendships are more intimate and they are substantially different from those that are not. We examin...
Article
Full-text available
In this paper, we exploit different facets of the Friends and Family study to deal with two personality-related tasks of paramount importance for the user modeling and ubiquitous computing fields. First, we propose and validate an approach for automatic classification of personality traits based on the ego-networks’ structural characteristics. Our...
Article
Background: Second opinion (SO) is common in medical practice and can reduce unnecessary risks and costs. To date, there is no population-based estimation of how many people seek SOs and what the characteristics of second-opinion seekers are. Objectives: To estimate how many people seek SOs, and what the characteristics of second-opinion seekers...
Article
Full-text available
Persuasion is at the core of norm creation, emergence of collective action, and solutions to ‘tragedy of the commons’ problems. In this paper, we show that the directionality of friendship ties affect the extent to which individuals can influence the behavior of each other. Moreover, we find that people are typically poor at perceiving the directio...
Data
Contains the following. Sections: 1 The Friends and Family Study, 2 The FunFit Experiment, 3 The Reciprocity Survey, 4 Directionality and Induced Peer Pressure, 5 Social Embeddedness, 6 Social Centrality, 7 Predicting Reciprocity and Directionality, 8 Reciprocal Ties and Incoming Edges Factors, 9 Additional Datasets. Table S1: numbers of participan...
Article
Active honeytokens are fake digital data objects planted among real data objects and used in an attempt to detect data misuse by insiders. In this article, we are interested in understanding how users (e.g., employees) behave when interacting with honeytokens, specifically addressing the following questions: Can users distinguish genuine data objec...
Article
Springer International Publishing Switzerland 2016. Friendship is a fundamental characteristic of human beings and usually assumed to be reciprocal in nature. Despite this common expectation, in reality, not all friendships by default are reciprocal nor created equal. Here, we show that reciprocated friendships are more intimate and they are substa...
Conference Paper
Full-text available
One highly studied aspect of social networks is the identification of influential nodes that can spread ideas in a highly efficient way. The vast majority of works in this field have investigated the problem of identifying a set of nodes, that if " seeded " simultaneously, would maximize the information spread in the network. Yet, the timing aspect...
Conference Paper
Full-text available
The proposed work offers a shift from a well-researched question " what node to seed " in order to increase information spread, to a question " what node at what time period to seed " in order to increase information spread in social networks. In our busy period, ideas compete on limited human attention resources, which thrive to cope with informat...
Conference Paper
Ride sharing’s potential to improve traffic congestion as well as assist in reducing CO2 emission and fuel consumption was recently demonstrated by works such as [1]. Furthermore, it was shown that ride sharing can be implemented within a sound economic regime, providing values for all participants (e.g., Uber). Better understanding the utilization...
Article
We study the problem of privacy preservation in sequential releases of databases. In that scenario, several releases of the same table are published over a period of time, where each release contains a different set of the table attributes, as dictated by the purposes of the release. The goal is to protect the private information from adversaries w...
Chapter
Optimizing the use of available resources is one of the key challenges in activities that consist of interactions with a large number of "target individuals", with the ultimate goal of affecting as many of them as possible, such as in marketing, service provision and political campaigns. Typically, the cost of interactions is monotonically increasi...
Article
The need to share data often conflicts with privacy preservation. Data obfuscation attempts to overcome this conflict by modifying the original data while optimizing both privacy and utility measures. In this paper we introduce the concept of Constrained Obfuscation Problems (COPs) which formulate the task of obfuscating data stored in relational d...
Article
Full-text available
The rise of smartphones and web services made possible the large-scale collection of personal metadata. Information about individuals' location, phone call logs, or web-searches, is collected and used intensively by organizations and big data researchers. Metadata has however yet to realize its full potential. Privacy and legal concerns, as well as...
Article
In this paper, we analyze and compare five traditional architectures for database encryption. We show that existing architectures may provide a high level of security, but have a significant impact on performance and impose major changes to the application layer, or may be transparent to the application layer and provide high performance, but have...
Article
Full-text available
Social scientists have long sought to understand why certain people, items, or options become more popular than others. One seemingly intuitive theory is that inherent value drives popularity. An alternative theory claims that popularity is driven by the rich-get-richer effect of cumulative advantage---certain options become more popular, not becau...
Conference Paper
Full-text available
Today, users share large amounts of information about them-selves on their online social networks. Besides the intended information, this sharing process often also "leaks" sensitive information about the users -and by proxy -about their peers. This study investigates the effect of awareness about such leakage of information on user behavior. In pa...
Article
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Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a...
Conference Paper
Spam in Online Social Networks (OSNs) is a systemic problem that imposes a threat to these services in terms of undermining their value to advertisers and potential investors, as well as negatively affecting users' engagement. In this work, we present a unique analysis of spam accounts in OSNs viewed through the lens of their behavioral characteris...
Article
Full-text available
Optimizing the use of available resources is one of the key challenges in activities that consist of interactions with a large number of “target individuals,” with the ultimate goal of “winning” as many of them as possible, such as in marketing, service provision, political campaigns, or homeland security. Typically, the cost of interactions is mon...