in other news
TRANSCRIPT
In Other NewsBroaden your horizons by reading like a writerCharlotte Greenan
Using a social network of journalists to recommend news articles from sections you wouldn’t click on.
How can we find articles you might like from sections that you wouldn’t normally look at?
How can we find articles you might like from sections that you wouldn’t normally look at?
? ?
DataTwitter API
47,000 network relations
Twitter and Guardian APIs
1,300 Guardian journalists
Guardian API
300 articles daily
(10,000+ total)
Transitivity
USER
JOURNALIST 1
JOURNALIST 2
likes to read
likes to read
might like to read?
How can transitivity help to solve our problem?
USERwho likes
sport
SPORT
SPORT
SPORT
Narrow horizons!
How can transitivity help to solve our problem?
USERwho likes
sport
SPORT
World
SPORT
SPORT
Music
TV
Politics
Business
SportBroad horizons!
User-based recommender algorithm
Initial recommendations Weighted k-nearest
neighbors
User input
User feedback
Updated recommendationsIncorporating upvotes as
additional weighted neighbors.
Journalist featuresNeighbourhood component
analysis
User-based recommender algorithmLeave-one-out cross validation
Initial recommendations Weighted k-nearest
neighbors
User input
51% more correct followees (than just
recommending most popular journalists).
Up to 59% more correct followees.
User feedback
Updated recommendationsIncorporating upvotes as
additional weighted neighbors.
Journalist featuresNeighbourhood component
analysis
Charlotte Greenan
Homophily
Transitivity
12 times as many
triangles as a random graph
Data◎ Articles from Guardian API.◎ Social network from Twitter
API.
Leave-one-out cross validationImprovement in correctly predicted ties by section
Neighbourhood component analysisTransforming similarities between sections
Before After
Neighbourhood component analysisTransforming similarities between sections
Linear transformation of vectors indicating number of articles per section. Choose linear transformation :
Recommendation algorithm
◎ k most similar journalists, (cosine similarity);◎ Journalists you like, (user feedback);◎ Journalists you don’t like, (user feedback).
◎ Order journalists by their score:
◎ Recommend journalists using order until all sections recommended (or score is zero).
Credits
Special thanks to all the people who made and released these awesome resources for free:◎ Simple line icons by Mirko Monti◎ E-commerce icons by Virgil Pana◎ Streamline iconset by Webalys◎ Presentation template by SlidesCarnival◎ Photographs by Unsplash & Death to the Stock Photo
(license)