- Published on Friday, 27 April 2018 19:21
In an article just published in EPJ Data Science, Valentin Kassarnig, Sune Lehmann and Andreas Bjerre-Nielsen look into smartphone data of undergraduate students to assess factors influencing social behavior and educational performance.
(Guest post by Valentin Kassarnig, Sune Lehmann & Andreas Bjerre-Nielsen, originally published on the SpringerOpen blog)
EPJ Data Science Highlight - Discovering temporal regularities in retail customers’ shopping behaviour
- Published on Wednesday, 18 April 2018 08:26
Why do we buy certain items when we buy them? A new study published in EPJ Data Science analyzes personal retail data to extract a temporal purchasing profile, which is able to summarize whether and when a customer makes a purchase. Its results show that certain patterns and types of shoppers are detectable, which can be used both by customers to enable personalized services, and by the retail market chain for providing offers and discounts tailored to the individual shoppers personal temporal profile.
(Guest post by Riccardo Guidotti and Anna Monreale, originally published on the SpringerOpen blog)
- Published on Tuesday, 10 April 2018 08:06
(This post was originally published on the SpringerOpen blog)
A team of researchers from Northeastern University, Boston, used a big data approach to investigate what makes a book successful. By evaluating data from the New York Times Bestseller Lists from 2008 to 2016, they developed a formula to predict if a book would be a bestseller.