Instagram posts offer a unique window into city life, highlighting urban spaces, revealing resident aspirations, and showcasing public activities. Our research project demonstrates that this social platform can serve as valuable data for urban research and analysis.
I developed a Python package to facilitate Instagram post extraction via API, which became the foundation of our research process. Working together with my Medialab team and researchers from Metropolitan Institute of Bratislava, we conducted:
- data preprocessing and cleaning for analysis,
- advanced visualization and pattern recognition,
- topic modeling and content categorization.
What our research revealed #
By analyzing thousands of posts from five distinctive Bratislava parks, we uncovered fascinating patterns in visitor behavior, park usage, and seasonal preferences. Our methods combined hashtag analysis, machine learning, and image recognition to identify:
- Seasonal visitation trends showing autumn’s popularity across most parks
- Unique park characteristics, from spring blooms to winter activities
- Implicit connections between visitor activities and emotional responses
- Shifting usage patterns during the pandemic period
- Park-specific themes and attractions
The research demonstrates how social media analysis can supplement traditional urban studies by revealing unconscious user patterns and sentiments. Our approach is particularly effective when comparing multiple spaces over time, providing insights that would be difficult to obtain through conventional surveys.
See in detail how we explored Bratislava parks using Python and Instagram API, and discover the comprehensive methodology behind extracting meaningful urban insights from social data.
Note: Unfortunately, the Instagram API used in this project to download posts is no longer available.