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Idea by

Elena Shmileva, Victor Sarzhan

https://www.hse.ru/en/org/persons/157498052

St.Petersburg, Russia
Elena Shmileva is an applied mathematician and associate professor from Higher School of Economics Campus in St.Petersburg, Russia. Victor Sarzhan is a student of a Master’s programme ‘Big Data Analysis for Business, Economy, and Society’, HSE, SPb.

Cluster analysis for studying communities in big cities.


Clusterization of checkins sequences from geo-social networks.

Cluster analysis for studying communities in big cities.


Clusterization of checkins sequences from geo-social networks.
We clusterize checkins sequences parsed from geosocial networks and study the properties of clusters (communities) that we obtain.
File under
Type of project
  • Systemic changes

The practical interest to this problem could be explained from sociological and technological side.
From the sociological viewpoint the clusters collect users with similar behaviour, i.e. show communities of citizens. So, this research would help sociologists to understand some attributes of these communities without doing expensive surveys. For example, our study helps to calculate sizes of communities or to understand typical consumer trajectories of people from the communities.
From the technological point of view our study helps to forecast the next point-of-interest for users.

Cluster analysis for studying communities in big cities.


Clusterization of checkins sequences from geo-social networks.

Cluster analysis for studying communities in big cities.


Clusterization of checkins sequences from geo-social networks.
We clusterize checkins sequences parsed from geosocial networks and study the properties of clusters (communities) that we obtain.
File under
Type of project
  • Systemic changes

The practical interest to this problem could be explained from sociological and technological side.
From the sociological viewpoint the clusters collect users with similar behaviour, i.e. show communities of citizens. So, this research would help sociologists to understand some attributes of these communities without doing expensive surveys. For example, our study helps to calculate sizes of communities or to understand typical consumer trajectories of people from the communities.
From the technological point of view our study helps to forecast the next point-of-interest for users.


Idea by

Elena Shmileva, Victor Sarzhan
St.Petersburg
Russia
Elena Shmileva is an applied mathematician and associate professor from Higher School of Economics Campus in St.Petersburg, Russia. Victor Sarzhan is a student of a Master’s programme ‘Big Data Analysis for Business, Economy, and Society’, HSE, SPb.