Knowledge about the reception of architectural structures is crucial for architects and urban planners. Yet obtaining such information has been a challenging and costly activity. However, with the advent of the Web, a vast amount of structured and unstructured data describing architectural structures has become available publicly. This includes information about the perception and use of buildings (for instance, through social media), and structured information about the building’s features and characteristics (for instance, through public Linked Data). Hence, first mining (i) the popularity of buildings from the social Web and (ii) then correlating such rankings with certain features of buildings, can provide an efficient method to identify successful architectural patterns. In this paper we propose an approach to rank buildings through the automated mining of Flickr metadata. By further correlating such rankings with building properties described in Linked Data we are able to identify popular patterns for particular building types (airports, bridges, churches, halls, and skyscrapers). Our approach combines crowdsourcing with Web mining techniques to establish influential factors, as well as ground truth to evaluate our rankings. Our extensive experimental results depict that methods tailored to specific structure types allow an accurate measurement of their public perception.

1. Ranking Buildings and Mining the Web
for Popular Architectural Patterns
Ujwal Gadiraju,
Stefan Dietze and Ernesto Diaz-Aviles
Oxford, 29th June 2015

2. Outline
● Motivation
● Background
● Methodology
● Results
● Conclusions
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3. Camillo Sitte
Main works are “an aesthetic criticism”
of 19th century urbanism.
The whole is much more than the sum
of it’s parts.
“City Planning according to artistic principles.”
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4. Form follows function VS Ornamentalism
Louis Sullivan
Father of Modernism.
Father of Skyscrapers.
“That life is recognizable in its
expression,
That form ever follows function.
This is the law.”
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5. Built Environment
Space
SyntaxIMPLICATIONS
● Urban planning
● Impact of an architectural structure
● Identify needs for restructuring, adequate
maintenance and trigger retrofit scenarios
● Predict impact of building projects
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6. What do people think about buildings?
● (On the way)/(at) home, work, play.
● Buildings invoke feelings [1,2].
● Research has established that buildings
shape the built environment.
● Built environment influences various
aspects within a community.
[1]. Brain electrical responses to high-and low-
ranking buildings. Oppenheim et al.
Clinical EEG and Neuroscience, 2009.
[2]. Hippocampal contributions to the processing
of architectural ranking. Oppenheim et al.
NeuroImage, 2010.
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7. Surveying Experts to establish Influential Factors
Building Types
- Skyscrapers
- Bridges
- Churches
- Halls
- Airports
Emerging factors :
● Historic importance
● Effect on/of the surroundings/built
environment
● Materials used
● Size of the building/structure
● Personal experiences
● Level of Details
Emerging factors :
- Ease of access to airport
- Efficiency of movement/
processing inside airport
- General design &
Appearance
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8. Crowdsourcing Ground Truth
● 5-point Likert Scale (Strongly Dislike - Strongly Like)
● Gold Standards and precautions to detect
and curtail malicious workers or bots [1].
● Images presented with same resolution
and dimensions [2].
● Avoid bias by using images from
Wikimedia Commons.
● 18,500 trusted responses from 7,396
workers.
[1]. Understanding Malicious Behavior on Crowdsourcing Platforms - The Case of Online Surveys.
Ujwal Gadiraju, Ricardo Kawase, Stefan Dietze and Gianluca Demartini. In Proceedings of the 33rd Annual
ACM Conference on Human Factors in Computing Systems. 2015.
[2]. "Size does matter: how image size affects aesthetic perception?." Chu, Wei-Ta, Yu-Kuang Chen,
and Kuan-Ta Chen. In Proceedings of the 21st ACM international conference on Multimedia. ACM, 2013.
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9. Emerging Influential Factors
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10. Processing Pipeline for Automated Ranking of Buildings
Crowdsourcing Web Mining
● News Articles and Blogs
● Tweets
● Meta-data from flickr
images (title, description,
tags favorites, comments)
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11. Automated Ranking-Workflow
Dataset
Characteristics
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12. Models for Ranking Buildings
● Based on perception-related metadata from relevant
Flickr images.
● Sentic feature vectors using EmoLex.
● RankSVM to learn model(s).
● Feature selection for construction of different models.
● Best performing model : Weighted Model (weighted
combination of feature vectors according to influential
factors)
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13. Properties
13
Influential
Factors
Ground Truth
(Crowdsourcing)
Ranking
Models
Ranked List
CORRELATE
Well-perceived patterns for Architectural Structures
top-k

14. DBpedia properties corresponding to Influential Factors
Caveat :
● Coverage of DBpedia
properties corresponding to
influential factors is limited
SIZE
dbpedia-owl:
runwayLength
dbpedia-owl:
Length
dbprop:
architectureStyle
dbprop:
seatingCapacity
dbpedia:
floorCount
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15. Consolidation of Patterns
CHURCHES: Best-perceived Architectural Styles
● Gothic Revival
● Romanesque
● Gothic
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16. Consolidation of Patterns
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17. Conclusions & Future Work
● Functionalism vs Ornamentalism?
● Correlating building rankings with structured data
from the Web can help us to establish popular
architectural patterns.
● Building type-specific methods are important.
● Multidimensional architectural patterns through
regression of influential factors.
● Using Web Data (both social and structured) in
order to fill in the missing gaps.
For example,
buildings with x size, y uniqueness, z
materials used, … are best perceived.
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18. Summary
● Identified Influential Factors for different
building types
● Ground truth construction via Crowdsourcing
● Models for ranking buildings automatically
● Correlated influential factors with structured
data from DBpedia
Well-perceived patterns for Architectural Structures
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19. Contact Details :
gadiraju@l3s.de
http://www.L3S.de
SLIDES:
http://www.slideshare.net/uj
wal07/
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20. Influential Factors for Airports
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21. America’s Favorite Architecture: AIA 150
● 2006-2007 AIA organized a study, carried out by Harris
Initiative
● In the first phase : 2,448 AIA members interviewed
● In the second phase: Survey of general public (2,214
people)
● Criticism :
o List of favorites did not reflect judgments of
architectural experts
o AIA President said, “Rankings reflected people’s
emotional connections to buildings”.
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22. Popularity vs Perception
● POPULARITY : The state of being liked, admired or being supported by
many people.
E.g. Do you KNOW this building?
● PERCEPTION : The way in which something is regarded, understood, or
interpreted.
E.g. Do you LIKE this building?
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23. Plutchik’s Psychoevolutionary Theory of Emotion
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