Projects per year
Abstract
Social connections and cultural aspects play important roles in shaping an individual’s preferences.
For instance, people tend to select friends with similar music preferences. Furthermore, preferences
and friending are influenced by cultural aspects. Recommender systems may benefit from these
phenomena by using knowledge about the nature of social ties to better tailor recommendations to an
individual. Focusing on the specifities of music preferences, we study user connections on Last.fm—an
online social network for music. We identify those countries whose users are mainly connected within
the same country, and those countries that are characterized by cross-country user connections.
Strong cross-country connection pairs are typically characterized by similar cultural, historic, or
linguistic backgrounds, or geographic proximity. The United States, the United Kingdom, and Russia
are identified as countries having a large relative amount of user connections from other countries.
Our results contribute to understanding the complexity of social ties and how they are reflected in
connection behavior, and are a promising source for advancements of personalized systems.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems ACM CHI '19 |
| Number of pages | 6 |
| Publication status | Published - May 2019 |
Fields of science
- 202002 Audiovisual media
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102003 Image processing
- 102015 Information systems
JKU Focus areas
- Digital Transformation
Projects
- 1 Finished
-
Fein-granulare kultur-bezogene Musikempfehlungssysteme
Bauer, C. (PI)
01.02.2017 → 31.01.2020
Project: Funded research › FWF - Austrian Science Fund