Algorithms can be very useful, especially when filtering through lots and lots of information. They can help us identify trends, quickly sum up popular concepts, and detect outliers at very early stages. I'd like to believe that my role as a data scientist is to give the digg editors superpowers - help them find quality content as early as possible. With the growing amount of information/content published, and people’s continued expectation that “news will find them”, there's no doubt we need to depend on algorithmic mechanisms. But we also need to design these algorithmic systems while questioning ourselves – what is it that we’re optimizing? Is it only “eyeballs” or is there a higher cause we should aim for? The choices that we make when designing these systems are like setting the rules of a game: they determine who wins and who loses.

1. Gilad Lotan | @gilgul
Chief Data Scientist, betaworks

3. UNWRA School Shooting

4. UNWRA School Shooting

5. UNWRA School Shooting

6. Homophily

7. Algorithmic Ranking

8. An algorithm is…
• Series
of
steps
taken
to
solve
a
par0cular
problem
• Given
an
input,
provides
an
output

9. • Iden0fy
popular
concepts
• Find
groups
of
similar
items
• Detect
outliers

10. Collaborative Filtering
likes
likes
A
B

11. Trending Topic:
Items that display abnormally high shares in a
relatively short time period

12. Term Frequency Inverse Document Frequency (TFIDF)

16. #OccupyWallStreet
Never
Trends
in
New
York

17. “News will find me”

19. Thank
You
gilad@betaworks.com
|
@gilgul