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Inequality Is Rising Where Social Network Segregation Interacts with Urban Topology

February 18, 2021
New paper by CEU DNDS alumnus Johannes Wachs and János Kertész with collaborators in Nature Communications.

Attention Dynamics on Sina Weibo during COVID-19 Pandemic

February 4, 2021
A new paper by Hao Cui and János Kertész in EPJ Data Science.
Understanding attention dynamics on social media during pandemics could help governments minimize the effects. We focus on how COVID-19 has influenced the attention dynamics on the biggest Chinese microblogging website Sina Weibo during the first four months of the pandemic. We study the real-time Hot Search List (HSL), which provides the ranking of the most popular 50 hashtags based on the amount of Sina Weibo searches.

Correlations of Socioeconomic and Urban Patterns Observed via an Interpretable Deep Learning Model

November 2, 2020

Urbanization is a great challenge for modern societies, promising better access to economic opportunities, but widening socioeconomic inequalities. Accurately tracking this process as it unfolds has been challenging for traditional data collection methods, but remote sensing information offers an alternative way to gather a more complete view of these societal changes. By feeding neural networks with satellite images, the socioeconomic information associated with that area can be recovered.

Interpretable Deep Learning Model for Socioeconomic Status Inference from Satellite Images and Their Correlations with Urban Patterns

November 2, 2020

Cities have become the economic bedrock of modern nations and this transition will likely be continued in the coming years as an estimated three billion people will move into cities by 2030. Nevertheless, while urbanisation can entail economic dynamism and social development, it can also create enormous social challenges. The management of natural hazards and pollution, the exclusion of the poor from the city’s socioeconomic fabric and the subsequent surge of social and economic inequalities have become some of the pressing issues that modern metropolises need to address.

Design Patterns of Social Bots

July 2, 2020

Our 2nd year PhD student Abdullah Alrhmoun presented his research project about the Design Patterns of Social Bots. Design patterns are a toolkit of tried and tested solutions to recurring (repetitive) design problems. Nowadays, the ecosystems of online bots are drastically increasing in number and complexity. An increasing amount of websites and online social networks are becoming the perfect environment for bots, operating dependently or not from users’ inputs.