Massachusetts Institute of Technology
The influence of collaboration networks on programming language acquisition
Abstract
dc:description.abstractMany behaviors spread through social contact. However, different behaviors seem to require different degrees of social reinforcement to spread within a network. Some behaviors spread via simple contagion, where a single contact with an "activated node" is sufficient for transmission, while others require complex contagion, with reinforcement from multiple nodes to adopt the behavior. But why do some behaviors require more social reinforcement to spread than others? Here we hypothesize that learning more difficult behaviors requires more social reinforcement. We test this hypothesis by analyzing the programming language adoption of hundreds of thousands of programmers on the social coding platform Github. We show that adopting more difficult programming languages requires more reinforcement from the collaboration network. This research sheds light on the role of collaboration networks in programming language acquisition.
Degree
thesis:*- Department dc:contributor.department
- Program in Media Arts and Sciences (Massachusetts Institute of Technology)
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2018
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Guruprasad, Sanjay
- Advisor dc:contributor.advisor
-
- César Hidalgo.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
- Licence dc:rights.uri
- Language dc:language.iso
- eng
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/1721.1/119085
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/119085