Conceptual syntagmatic associations in user tagging

Yoon, Kyunghye

doi:10.1002/asi.22601

Cited by 7 publications

(5 citation statements)

References 34 publications

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“…This study attempts to investigate on whether syntagmatic relation and paradigmatic association can exist at the same time empirically, and tries to reveal how these two relations relate with each other. Assigned MeSH descriptors are used to represent syntagmatic relations as in (Yoon, 2012). Their paradigmatic relations are determined according to the structure of the MeSH thesaurus.…”

Section: Literature Reviewmentioning

confidence: 99%

Paradigmatic relations and syntagmatic relations: How are they related?

Chiu

Lü

2015

Proc. Assoc. Info. Sci. Tech.

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This study investigates the relationship between syntagmatic and paradigmatic relations. MeSH (Medical Subject Headings) descriptors assigned to the same document are chosen to represent the syntagmatic relations and their paradigmatic relations are determined using the structure of the MeSH thesaurus. With the help of MeSH tree structure, we determined the paradigmatic relations between each pair of assigned descriptors for each document (if there is any). The results show that paradigmatic relations and syntagmatic relations can coexist, but it is not very common. Only 13.56% of the pairs of descriptors are connectable on the MeSH tree, and thus can be said to have some paradigmatic relations. It generally takes 3 to 5 steps on the tree for these pairs of descriptors to reach each other. The results also show that the strength of the paradigmatic relations depends on the specificity of the descriptors. The more specific a pair of descriptors are, the stronger paradigmatic relations they are likely to have. When the assigned descriptors are very general, they are less likely to have strong paradigmatic relations (e.g. parent-child or siblings relations). The findings of this study can help better use of sematic relations for different applications such as ontology construction, information extraction, information retrieval, question-answering, and text summarization.

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Section: Literature Reviewmentioning

confidence: 99%

Paradigmatic relations and syntagmatic relations: How are they related?

Chiu

Lü

2015

Proc. Assoc. Info. Sci. Tech.

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“…Whereas paradigmatic relationships are defined a priori, as in the formal structure of an ontology, syntagmatic relationships can only be defined a posteriori, originating in the actual occurrence of terms within texts (Khoo & Na, 2006;Peters & Weller, 2008;Stock, 2010). Several studies have suggested that understanding how individuals employ syntagmatic relationships can illuminate how they classify information in online environments (Yoon 2012), create formalized structures of meaning through indexing (Olsen & Wolfram, 2008), and represent information at the conceptual level (Green, 1995b;1995c;Khoo & Na, 2006). At a basic level, syntagmatic relationships create core semantic meanings within texts via relationships between "topic," or that which the textual unit is about, and "comment," or that upon which the text elaborates (Jakobson, 1963;Yoon, 2012).…”

Section: Syntagmatic Relations In Discourse Analysismentioning

confidence: 99%

“…Several studies have suggested that understanding how individuals employ syntagmatic relationships can illuminate how they classify information in online environments (Yoon 2012), create formalized structures of meaning through indexing (Olsen & Wolfram, 2008), and represent information at the conceptual level (Green, 1995b;1995c;Khoo & Na, 2006). At a basic level, syntagmatic relationships create core semantic meanings within texts via relationships between "topic," or that which the textual unit is about, and "comment," or that upon which the text elaborates (Jakobson, 1963;Yoon, 2012). Breaking down user claims into syntagmatic topic/comment relationships provides a systematic process for analyzing how the topic being addressed may be consistent across individual reviews, yet its meaning might change subtly or develop further depending on the comments made about it.…”

Section: Syntagmatic Relations In Discourse Analysismentioning

confidence: 99%

Using syntagmatic relations to examine semantic communities in user generated book reviews

Yoon

Bezdicek

2015

Proc. Assoc. Info. Sci. Tech.

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While several studies have suggested that implicit semantic communities can be identified within user generated content, the majority have focused on identifying these communities via networks of "tags" within folksonomies. This method can be problematic due to the lack of linguistic context inherent in tags as collections of discrete terms. This study attempted a different approach to this problem by analyzing a corpus of user generated reviews for popular science books taken from Amazon. It searched the reviews for patterns of shared core semantic meanings as constituted by syntagmatic relations between "topic" and "comment." Preliminary results showed that (1) core semantic meanings expressed via "topic" and "comment" relations were salient across reviews for a given book and across books within the genre and (2) specific patterns of core semantic meanings suggested the presence of different user communities constituted through similar manners of commenting on the books. The results provide insight into the social ways that readers accumulate shared meaning around books through repetition, interpretation, annotation.

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“…Semantics techniques have been used to link social tags to a controlled vocabulary (Yi, ) and deploy tag analysis to uncover semantic relations (Yoon, ). A prominent theme is semantic tagging for aggregation and analysis.…”

Section: Introductionmentioning

confidence: 99%

Ontology for cultural variations in interpersonal communication: Building on theoretical models and crowdsourced knowledge

Thakker

Karanasios

Blanchard³

et al. 2017

Asso for Info Science & Tech

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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.

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Conceptual syntagmatic associations in user tagging

Cited by 7 publications

References 34 publications

Paradigmatic relations and syntagmatic relations: How are they related?

Paradigmatic relations and syntagmatic relations: How are they related?

Using syntagmatic relations to examine semantic communities in user generated book reviews

Ontology for cultural variations in interpersonal communication: Building on theoretical models and crowdsourced knowledge

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