[Talk @ CSSWS in Cologne - December 2015] Experiencing food is something that involves all five senses. Can we sense a city, as we sense food? With Luca and Daniele few years ago, we started to focus on understanding how people psychologically perceive the city. We used social media data to create new maps that find not only the shortest, but also the most enjoyable path based on aesthetics. Building upon the visual layer, we recently proposed a methodology to capture the entire smellscape of a city and not only the bad odors typically the focus on urban planners. We proposed the first urban smell dictionary organized on 10 main smell categories. By looking at pictures shared in social media platforms we can map the different smell in the city. We also produce an interactive map that is available at goodcitylife.org where you can click on a street to see its smell profile. We all know that social media data is biased, we tried to validate our approach using complementary data sources from city officials or from mapping platform like open street map. We correlate the presence of certain smell clusters and air quality indicators at the level of street segment. We studied also the correlation between a street segment’s smell category and OSM natural tags. Adding another sensorial level, we plan to model urban sound. City planning is concerned mainly with noise, not least because both pleasant and unpleasant sounds are difficult to record and analyze at city scale. Similarly to smell, we proposed the first urban sound dictionary organized in 6 main source categories and we are working on ChattyMaps, a new layer of interactive cartography for the exploration of urban soundscapes. Smell has a considerable effect on our emotions. The same goes for sound. We set out to study this effect. To this end, we first used the LIWC dictionary and in particular the words in the positive and negative emotions categories and we matched them with tags attached to geo-located photos. The result is a map weighted by sentiment. We correlated this sentiment score with the presence of certain smells categories we found that positive sentiment tags are mainly present in streets with food and nature smells and negative sentiment tags are mainly associated with waste and metro smells. To model sentiment with a finer-grained level, we adopted also the EmoLex lexicon that follows the 8 primary emotions from Plutchik’s psychoevolutionary theory. We map those dimensions and we correlate them to the presence of smell and sound. We found that joy positively correlates with food and nature and negatively with emissions and waste. Joyful words are associated with streets typically characterized by music and human sounds, while they are absent in streets with traffic. Interestingly, we found also that music sounds are strongly connected to sadness that shows how music triggers a wide spectrum of emotional responses. reference: http://www.goodcitylife.org

1. MAPPING THE SENSORIAL
LAYERS OF A CITY
ROSSANO SCHIFANELLA
GESIS CSSWS, COLOGNE

2. Experiencing food involves all senses.

4. Can we sense a city, as we sense food?

6. Happy Maps

7. SIGHT
S
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8. URBAN SMELL

9. URBAN SMELLSCAPE AROMA WHEEL

11. SIGHT
SMELL
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12. VALIDATION
OSM
(presence of food, nature)
CITY OFFICIALS
(air quality)

13. 0,47
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NO2 PM10 PM2,5
AIR POLLUTION vs SMELL in
LONDON
Emissions Nature
correlation

14. -0,20
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OSM NATURAL TAGS
emissions nature
# of tags for street segment
correlation

15. -0,10
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OSM FOOD TAGS
food
# of tags for street segment
correlation

16. URBAN SOUND

17. URBAN SOUNDSCAPE WHEEL

18. Chatty Maps

19. SIGHT
SMELL
SOUND S
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21. SIGHT
SMELL
LIWC
SOUND S
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23. 0,25
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Nature Food Metro Waste
SMELL vs SENTIMENT
correlation

24. Plutchik’s primary
emotions
EmoLex dictionary

25. SIGHT
SMELL
LWIC
EMOLEX
SOUND S
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26. WASTE
EMISSIONS FOOD
NATURE

27. MUSIC HUMAN