Activity bias for selected (ATKIS) Land use categories (DE)
Actvity bias for selected (ATKIS) Land use categories (DE)
Intersection of 30M Social Media Posts with Land Use Categories
- Result: Landuse-Activity Heatmap
- Jupyter Notebook (HTML) for DE-Intersection and LBSM Data (1st step)
- Jupyter Notebook (HTML) for creating activity heatmap for ATKIS land use categories (2nd step)
- 2nd Jupyter Notebook Download
Activities are defined parametric by sets of terms and emoji:
topics['hiking'] = ('hike', 'hiking', 'wandern', 'wanderung', 'wanderer', 'wanderweg', 'wanderroute', '🥾') # optional: 🚶 (person walking)
# biking, this is a very specific ativity
topics['biking'] = ('bike', 'biking', 'bicycle', 'cycling', 'fahrrad', 'velo', '🚲', '🚴')
# just plain walking
topics['walking'] = ('walk', 'walking', 'spazieren', 'stroll', 'fußweg', 'spazierweg', 'spaziergang') # optional: 🚶 (person walking)
# broad category with a bias towards jogging
topics['sport'] = ('sport', 'jogging', 'running', 'exercise', 'run', 'workout', 'rennen', 'dauerlauf', '🏃')
topics['relaxing'] = ('relaxing', 'sitting', 'relaxation', 'entspannen', 'innehalten', 'erholen', 'ausruhen', 'recreation')
# meeting with friends, this can encompass a group of activities
# note that we use 'meeting'; in green-space land use, this likely hints to meeting with friends, not within work environment
topics['friends'] = ('friends', 'friends', 'meeting', 'socialize', 'freunde', 'treffen', 'hang around', 'abhängen')
# anything related to family and kinder/kids
topics['family'] = ('family', 'familie', 'kinder', 'baby', 'familienausflug', 'familytrip', '👪')
# tourist/sighseeing group
topics['tourist'] = ('tourist', 'sighseeing', 'sehenswürdigkeit', 'excursion', 'exkursion', 'sight-seeing', 'tour', 'travel', 'reise', '🌇')
# very general: spielen/playing
topics['playing'] = ('spielen', 'playing', 'play', 'spiel', 'game', '🎲', '🎮')
# lets add some specific activities: picknick-grillen, soccer ..
topics['picnic'] = ('picnic', 'barbecure', 'picknick', 'picknickkorb', 'grillen', 'grill')
topics['soccer'] = ('soccer', 'fussball', 'fußball', 'football', '⚽')