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  • × author_ss:"Lau, L."
  • × year_i:[2010 TO 2020}
  1. Thakker, D.; Karanasios, S.; Blanchard, E.; Lau, L.; Dimitrova, V.: Ontology for cultural variations in interpersonal communication : building on theoretical models and crowdsourced knowledge (2017) 0.03 
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    Abstract
    The domain of cultural variations in interpersonal communication is becoming increasingly important in various areas, including human-human interaction (e.g., business settings) and human-computer interaction (e.g., during simulations, or with social robots). User-generated content (UGC) in social media can provide an invaluable source of culturally diverse viewpoints for supporting the understanding of cultural variations. However, discovering and organizing UGC is notoriously challenging and laborious for humans, especially in ill-defined domains such as culture. This calls for computational approaches to automate the UGC sensemaking process by using tagging, linking, and exploring. Semantic technologies allow automated structuring and qualitative analysis of UGC, but are dependent on the availability of an ontology representing the main concepts in a specific domain. For the domain of cultural variations in interpersonal communication, no ontological model exists. This paper presents the first such ontological model, called AMOn+, which defines cultural variations and enables tagging culture-related mentions in textual content. AMOn+ is designed based on a novel interdisciplinary approach that combines theoretical models of culture with crowdsourced knowledge (DBpedia). An evaluation of AMOn+ demonstrated its fitness-for-purpose regarding domain coverage for annotating culture-related concepts mentioned in text corpora. This ontology can underpin computational models for making sense of UGC.
  2. Karanasios, S.; Thakker, D.; Lau, L.; Allen, D.; Dimitrova, V.; Norman, A.: Making sense of digital traces : an activity theory driven ontological approach (2013) 0.02 
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    Abstract
    Social web content such as blogs, videos, and other user-generated content present a vast source of rich "digital-traces" of individuals' experiences. The use of digital traces to provide insight into human behavior remains underdeveloped. Recently, ontological approaches have been exploited for tagging and linking digital traces, with progress made in ontology models for well-defined domains. However, the process of conceptualization for ill-defined domains remains challenging, requiring interdisciplinary efforts to understand the main aspects and capture them in a computer processable form. The primary contribution of this article is a theory-driven approach to ontology development that supports semantic augmentation of digital traces. Specifically, we argue that (a) activity theory can be used to develop more insightful conceptual models of ill-defined activities, which (b) can be used to inform the development of an ontology, and (c) that this ontology can be used to guide the semantic augmentation of digital traces for making sense of phenomena. A case study of interpersonal communication is chosen to illustrate the applicability of the proposed multidisciplinary approach. The benefits of the approach are illustrated through an example application, demonstrating how it may be used to assemble and make sense of digital traces.

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