Cynthia S Q Siew
Biographic Data
| ID | 1861463 |
|---|---|
| NAME | Cynthia S Q Siew |
| GIVEN NAMES | Cynthia S Q |
| FAMILY NAME | Siew |
| SIGNATURE | SIEW C S Q |
| AFFILIATIONS | National University of Singapore |
| ORCID | 0000-0003-3384-7374 |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 1 |
| WORKS AS AUTHOR | 10 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Comparing the influence of phonological network structure on spoken word recognition performance across speakers of North American and Singapore English
The mental lexicon is a repository of all known words and their phonological connections in long-term memory. These connectivity patterns can be visualized through phonological networks, with network metrics (degree and local clustering coefficient) having previously been observed to influence spoken word recognition. However, it remains unclear whether different dialects of a language have distinct phonological networks and whether such differen…
What we mean when we say semantic
Tulving characterized semantic memory as a vast repository of meaning that underlies language and many other cognitive processes. This perspective on lexical and conceptual knowledge galvanized a new era of research undertaken by numerous fields, each with their own idiosyncratic methods and terminology. For example, “concept” has different meanings in philosophy, linguistics, and psychology. As such, many fundamental constructs used to delineate…
Production and Perception Errors From Speech Error Corpora Reflect Macro- and Meso-Level Structure of the Phonological Language Network
The goal of the present study was to investigate if cognitive traces of the network structure of the phonological language network, where phonological word-form neighbors are connected to each other, could be uncovered in word substitution errors. The phonological network has a set of macro-level (i.e., features characterizing global structure of the lexicon) and meso-level (i.e., features characterizing intermediate structure or subgroups within…
Larger lexicons enable representation of fine-grained phonological similarity structure
Native English speakers are sensitive to the small-world structure and community structure of the phonological similarity network of English words. In this study we investigated whether L2 speakers of English are sensitive to the overall similarity structure of the phonological lexicon, and whether this sensitivity is modulated by the size of their L2 vocabulary. Participants with diverse L1s (with English as their L2) completed a phonological si…
Measuring the semantic priming effect across many languages
Syllable and letter similarity effects in Korean
Applications of Network Science to Education Research
A fundamental goal of education is to inspire and instill deep, meaningful, and long-lasting conceptual change within the knowledge landscapes of students. This commentary posits that the tools of network science could be useful in helping educators achieve this goal in two ways. First, methods from cognitive psychology and network science could be helpful in quantifying and analyzing the structure of students’ knowledge of a given discipline as …
Cognitive Network Science
Network science provides a set of quantitative methods to investigate complex systems, including human cognition. Although cognitive theories in different domains are strongly based on a network perspective, the application of network science methodologies to quantitatively study cognition has so far been limited in scope. This review demonstrates how network science approaches have been applied to the study of human cognition and how network sci…
Spreadr
The notion of spreading activation is a central theme in the cognitive sciences; however, the tools for implementing spreading activation computationally are not as readily available. This article introduces the spreadr R package, which can implement spreading activation within a specified network structure. The algorithmic method implemented in the spreadr subroutines follows the approach described in Vitevitch, Ercal, and Adagarla (Frontiers in…
Filling gaps in early word learning
Filling gaps in early word learning
Cognitive Network Science
Network science provides a set of quantitative methods to investigate complex systems, including human cognition. Although cognitive theories in different domains are strongly based on a network perspective, the application of network science methodologies to quantitatively study cognition has so far been limited in scope. This review demonstrates how network science approaches have been applied to the study of human cognition and how network sci…
Spreadr
The notion of spreading activation is a central theme in the cognitive sciences; however, the tools for implementing spreading activation computationally are not as readily available. This article introduces the spreadr R package, which can implement spreading activation within a specified network structure. The algorithmic method implemented in the spreadr subroutines follows the approach described in Vitevitch, Ercal, and Adagarla (Frontiers in…
Applications of Network Science to Education Research
A fundamental goal of education is to inspire and instill deep, meaningful, and long-lasting conceptual change within the knowledge landscapes of students. This commentary posits that the tools of network science could be useful in helping educators achieve this goal in two ways. First, methods from cognitive psychology and network science could be helpful in quantifying and analyzing the structure of students’ knowledge of a given discipline as …
Syllable and letter similarity effects in Korean
What we mean when we say semantic
Tulving characterized semantic memory as a vast repository of meaning that underlies language and many other cognitive processes. This perspective on lexical and conceptual knowledge galvanized a new era of research undertaken by numerous fields, each with their own idiosyncratic methods and terminology. For example, “concept” has different meanings in philosophy, linguistics, and psychology. As such, many fundamental constructs used to delineate…
Production and Perception Errors From Speech Error Corpora Reflect Macro- and Meso-Level Structure of the Phonological Language Network
The goal of the present study was to investigate if cognitive traces of the network structure of the phonological language network, where phonological word-form neighbors are connected to each other, could be uncovered in word substitution errors. The phonological network has a set of macro-level (i.e., features characterizing global structure of the lexicon) and meso-level (i.e., features characterizing intermediate structure or subgroups within…
Larger lexicons enable representation of fine-grained phonological similarity structure
Native English speakers are sensitive to the small-world structure and community structure of the phonological similarity network of English words. In this study we investigated whether L2 speakers of English are sensitive to the overall similarity structure of the phonological lexicon, and whether this sensitivity is modulated by the size of their L2 vocabulary. Participants with diverse L1s (with English as their L2) completed a phonological si…
Measuring the semantic priming effect across many languages
Comparing the influence of phonological network structure on spoken word recognition performance across speakers of North American and Singapore English
The mental lexicon is a repository of all known words and their phonological connections in long-term memory. These connectivity patterns can be visualized through phonological networks, with network metrics (degree and local clustering coefficient) having previously been observed to influence spoken word recognition. However, it remains unclear whether different dialects of a language have distinct phonological networks and whether such differen…
Computer Science (8 works) · Psychology (8 works) · Cognition (6 works) · Natural language processing (6 works) · Neurobiology of Language and Bilingualism (6 works) · Artificial Intelligence (5 works) · Linguistics (5 works) · Lexicon (4 works) · Language, Metaphor, and Cognition (3 works) · Phonology (3 works)