1. Recommender System for Pricing Contemporary Fine Art
Laurel Powell, Anna GELICH, & ZBIGNIEW W. RAS

2. Outline Introduction Current Art Market Recommender Systems
Pricing in the Art Market
Recommender Systems
Preliminary Work
Proposed Future Work

3. Contemporary Art Market
Multi-billion dollar industry
63.7 Billion USD in 2017
More galleries closed than opened
29% of sales take place online
Price transparency key concern of online buyers
Reference :

4. Why is art priced how it is?
Gallerists use connections and experience
Social Narratives
Economic Perspective
Collector Types
Superstars
Context
Why is art priced how it is?

5. Recommender Systems What is a recommender system?
Recommender System Types
Collaborative Filtering
Content Based
Demographic
Group
Knowledge Based
Hybrid

6. Art and Recommender Systems
Recommending similar artworks
Style, genre, artist
Predicting next purchase
Predicting next user interaction
Pricing contemporary art

7. Preliminary Work Dataset Features Developed and Tested Conclusions
Word Count
Social Media
Paragraph Vector
Sentiment Analysis
Conclusions

8. Dataset Scraped from Artfinder.com Approximately 200,000 artworks
2800 artists
60 countries
About Pages
Artwork Pages
Reviews

9. Price Distribution Maximum 1,000,000 USD Minimum 12.97 USD
Figure omits works priced at greater than 5000 USD due to scale

10. Base Features artistID artistCountry artwork_height artwork_width
authentication
medium
style
subject

11. Confusion Matrix with Base Features

12. Word Counts

13. Biography Word Count

14. Description word count

15. Title Word count

16. Social Media

17. Facebook

18. Twitter

19. Instagram

20. Text Clustering
Awards
Biography
Description
Education
Events
Title

21. Text Clustering Paragraph Vector 10, 25 and 50 Clusters
Also known as Doc2Vec
Extension of Word2Vec
10, 25 and 50 Clusters
Biography, Awards, Events and Education most impactful

22. 10 Clusters

23. 25 Clusters

24. 50 Clusters

25. Sentiment Analysis VADER Biography, Description, Title
Valence Aware Dictionary for sEntiment Reasoning
Rules and Lexicon
Biography, Description, Title

26. Sentiment

27. Positive Sentiments in Biography
Limited positive sentiment

28. Neutral Sentiments in Biography
Strong neutral sentiment

29. Negative Sentiments in Biography
Little to no negative sentiment

30. Sentiment in Description
Strong tendency toward neutral description
Almost no negative sentiment

31. Sentiment in Title Almost entirely neutral
No notable positive or negative sentiment

32. Combined Features AUC CA F1 Precision Recall Base Features 0.938 0.667
0.664
0.663
BF, Social, Word Counts
0.942
0.681
0.677
0.676
BF, Social, Word Counts, Clusters (10)
0.943
0.678
0.674
BF, Social, Word Counts, Clusters (25)
0.944
0.68
0.675
BF, Social, Word Counts, Clusters (50)
0.945
0.683
0.679
BF, Social, Word Counts, Sentiment
0.689
0.685
0.684
BF, Social, Word Counts, Sentiment, Clusters (50)
0.947
0.69
Combined Features

33. Confusion Matrix with Base Features and All Added Features