Abstract
Most social networks offer users to mark the current geolocation and link it to published posts. We propose a method for determining the general topic image of the area using such posts. Our method includes Data Splitting, Text Preprocessing, Record Filtration, Topic Modeling, segmentation, and aggregation. To demonstrate the approach, 5.46 million geotagged posts were collected for Saint Petersburg, Russia. As a result of the proposed method, after filtering, 2.65 million non-advertising posts are left, for which 10583 topics are found (4287 aggregated topics). In addition, the city is divided into clusters of attractions and districts based on data, which help to find the real points of interest of the city.
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