Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/230319
Title: EMOTION NETWORKS: A PSYCHOLINGUISTIC AND NETWORK SCIENCE APPROACH TO UNDERSTANDING EMOTIONS AND PSYCHOLOGICAL DISTRESS.
Authors: NICOLE KUEK MIN YEE
Keywords: Psychological distress
Emotion
Language
Network Science
Psycholinguistics
Issue Date: 16-May-2022
Citation: NICOLE KUEK MIN YEE (2022-05-16). EMOTION NETWORKS: A PSYCHOLINGUISTIC AND NETWORK SCIENCE APPROACH TO UNDERSTANDING EMOTIONS AND PSYCHOLOGICAL DISTRESS.. ScholarBank@NUS Repository.
Abstract: Psychological distress is complexly associated with emotional processes that are subsequently predictive of physical and psychological wellbeing. These associations to emotions have been echoed in language use of individuals in distress, yet the precise nature of the affective language of distress remains unclear. With computational advancements, network science and psycholinguistic approaches offer opportunities to further understand psychological distress, language and emotions. This study utilizes a novel cross-disciplinary approach to map the emotional lexicon and analyse its associations to psychological distress. 264 English-speaking undergraduates completed an emotion verbal fluency task and self- reported distress questionnaire. Z-tests were conducted on emotional lexicon content (e.g., arousal, valence, verbal productivity) of individuals with elevated distress and the full recruited sample. Network estimation techniques were utilized to construct emotion networks from individuals with elevated distress. 10,000 emotion networks constructed from 10,000 randomly sampled groups from full recruited sample form a null distribution. Binomial tests were conducted on measures of emotional lexicon network structure and organization (e.g., modularity, interconnectivity, centrality) in individuals with elevated distress and null distribution. Emotional lexicon content did not significantly differ. However, individuals with elevated distress exhibited differences in network structure and organization; specifically, (a) less overall network connectivity, indicating less accessibility to emotional concepts overall, (b) greater modularity, indicating increased difficulties traversing out of certain emotion concepts (i.e., “fear”, “upset”), and (c) different patterns of connectivity in specific emotions. Implications to the understanding of emotion and distress, and potential applications to future clinical research are discussed.
URI: https://scholarbank.nus.edu.sg/handle/10635/230319
Appears in Collections:Master's Theses (Restricted)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
2120_A0116699M.pdf1.58 MBAdobe PDF

RESTRICTED

NoneLog In

Page view(s)

33
checked on Dec 1, 2022

Download(s)

3
checked on Dec 1, 2022

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.