Sylabus
Session
Topic
Required Readings 1
Introduction: What is a network? 2
Network properties
Barabási, 2016: chapter 1
Castro & Siew, 2020 3
Lexical networks: Phonological word forms
Vitevitch et al., 2014
Vitevitch & Sommers, 2003 4
Constructing phonological networks
Gephi, R 5
Lexical networks: Semantics
De Deyne et al., 2017
Kang et al., 2017
Mak & Twitchell, 2020 6
Constructing semantic networks
Stella et al., 2017 7
Statistical analysis of network data (regression, mixed effects models)
Brown, 2021 8
Language change from the network perspective
Luef, Resnik, & Gráf, forthcoming
Milroy, 2004
Milroy & Milroy, 1985 9
Information propagation in social networks: Spreading gossip and rumors
Borgatti & Halgin, 2011
Yucel et al., 2020 10
Communication accommodation in social networks
Noble & Fernandez, 2015
Rienties et al, 2013 11
Lexical network growth
Hills et al., 2009
Luef, 2022
Siew & Vitevitch, 2020 12
Student presentations 13
Student presentations
Anotace
In recent years, interest in modeling and analyzing psychological phenomena, such as language and lexical memory, with the tools of network science has been on the rise and a considerable body of research in this area has been accumulated. Network science was developed to measure and represent statistical dependencies between connected entities and provides a powerful computational approach to quantify dyadic relationships. A network is made up of nodes, which represent the basic unit of the system and links, or edges, which signify the relations between them. Linguistic networks can be based on various concepts, for instance phonological word forms, semantics, or social partners involved in communication. This class examines the relevance of network science for the study of language on various levels of analysis. We will review efforts to construct different types of language networks, characterize properties of those networks, and apply statistical analyses to elucidate the structure and complex relationships of entities within the networks.
In the summer semester 2024 this course will be taught online using the platform Teams. Please make sure that you have a university Teams account to participate. Students can either attend the course online from room P111 - which will be reserved during course time - or join from home.