Erez Shmueli
Biographic Data
| ID | 5534520 |
|---|---|
| NAME | Erez Shmueli |
| GIVEN NAMES | Erez |
| FAMILY NAME | Shmueli |
| SIGNATURE | SHMUELI E |
| AFFILIATIONS | Tel Aviv University |
| ORCID | 0000-0003-3193-5768 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Influence Maximization Through Scheduled Seeding in a Real-World Setting
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 to infect nodes. Then, we examine the potential of a scheduled seeding strategy by analyzing a real…
Bayesian collective learning emerges from heuristic social learning
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 alone. However, groups of people face two coupled challenges in accumulating knowledge to make good …
Timing Matters
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 processes, and different solutions were suggested for maximizing influence under such models. However, m…
Second Medical Opinion
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 are. METHODS: We conducted both a medical records analysis (n=1,392,907) and a cross-sectional nationa…
No prominent works on this page.
Second Medical Opinion
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 are. METHODS: We conducted both a medical records analysis (n=1,392,907) and a cross-sectional nationa…
Timing Matters
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 processes, and different solutions were suggested for maximizing influence under such models. However, m…
Bayesian collective learning emerges from heuristic social learning
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 alone. However, groups of people face two coupled challenges in accumulating knowledge to make good …
Influence Maximization Through Scheduled Seeding in a Real-World Setting
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 to infect nodes. Then, we examine the potential of a scheduled seeding strategy by analyzing a real…
Computer Science (3 works) · Mathematics (3 works) · Opinion Dynamics and Social Influence (3 works) · Complex Network Analysis Techniques (2 works) · Engineering (2 works) · Evolutionary Game Theory and Cooperation (2 works) · Mathematical optimization (2 works) · Maximization (2 works) · Population (2 works) · Seeding (2 works)