The influence of collaboration networks on programming language acquisition
Name
1057897623-MIT.pdf
Description
Full printable version
Size
2.43 MB
Format
Adobe PDF
Checksum (MD5)
bb80aa96f647c7dc0e62b2c7bab6f1e2
Author(s)
Guruprasad, Sanjay
Advisor(s)
César Hidalgo.
Date Issued
2018
Publisher
Massachusetts Institute of Technology
Abstract
Many 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.
Description
Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 26-28).
Subjects
Program in Media Arts and Sciences ()
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
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