Traditional models assume a simple rule: people connect with others like them. But our research goes further. We’ve created a model that separates local homophily—strong bonds within close-knit groups—from global homophily, the weaker links across broader communities. This distinction helps explain complex social behaviors and how they impact network dynamics.
Using a maximum entropy approach, our model quantifies these layers of homophily and their influence on networks. One key finding is that different levels of homophily lead to unique percolation behaviors—shifts in how networks stay connected or fragment under certain conditions. We also discovered that these interactions affect critical thresholds for spreading phenomena, from viral outbreaks to information diffusion.
By applying our model to diverse real-world datasets, we demonstrated its ability to capture fine-grained patterns in networks. The insights go beyond theory—they have real implications for designing better public health interventions, optimizing information campaigns, and understanding the role of community structures in amplifying or limiting spread.
So, if you are looking for a network model that distinguishes between [local] homophily within small groups and [global] homophily across larger, more diverse communities, you shall not miss our new pre-print: https://arxiv.org/abs/2412.07901
Traditional models assume a simple rule: people connect with others like them. But our research goes further. We’ve created a model that separates local homophily—strong bonds within close-knit groups—from global homophily, the weaker links across broader communities. This distinction helps explain complex social behaviors and how they impact network dynamics.
Using a maximum entropy approach, our model quantifies these layers of homophily and their influence on networks. One key finding is that different levels of homophily lead to unique percolation behaviors—shifts in how networks stay connected or fragment under certain conditions. We also discovered that these interactions affect critical thresholds for spreading phenomena, from viral outbreaks to information diffusion.
By applying our model to diverse real-world datasets, we demonstrated its ability to capture fine-grained patterns in networks. The insights go beyond theory—they have real implications for designing better public health interventions, optimizing information campaigns, and understanding the role of community structures in amplifying or limiting spread.
So, if you are looking for a network model that distinguishes between [local] homophily within small groups and [global] homophily across larger, more diverse communities, you shall not miss our new pre-print: https://arxiv.org/abs/2412.07901
BY Complex Systems Studies
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Messages are not fully encrypted by default. That means the company could, in theory, access the content of the messages, or be forced to hand over the data at the request of a government. This provided opportunity to their linked entities to offload their shares at higher prices and make significant profits at the cost of unsuspecting retail investors. Telegram Messenger Blocks Navalny Bot During Russian Election At the start of 2018, the company attempted to launch an Initial Coin Offering (ICO) which would enable it to enable payments (and earn the cash that comes from doing so). The initial signals were promising, especially given Telegram’s user base is already fairly crypto-savvy. It raised an initial tranche of cash – worth more than a billion dollars – to help develop the coin before opening sales to the public. Unfortunately, third-party sales of coins bought in those initial fundraising rounds raised the ire of the SEC, which brought the hammer down on the whole operation. In 2020, officials ordered Telegram to pay a fine of $18.5 million and hand back much of the cash that it had raised. Telegram was co-founded by Pavel and Nikolai Durov, the brothers who had previously created VKontakte. VK is Russia’s equivalent of Facebook, a social network used for public and private messaging, audio and video sharing as well as online gaming. In January, SimpleWeb reported that VK was Russia’s fourth most-visited website, after Yandex, YouTube and Google’s Russian-language homepage. In 2016, Forbes’ Michael Solomon described Pavel Durov (pictured, below) as the “Mark Zuckerberg of Russia.”
from pl
