Abstract
Semantic networks are graphical representations, in terms of nodes and edges, of words and phrases from the linguistics vocabulary to form a meaning and relation between them to describe the intended target or object. It is part of the computer science field utilising Natural Language Processing, text mining, psychology, and sociology. The edges may describe the relation between the nodes as weak or strong, or one way or both ways, or if the node is stand alone. Semantic networks use datasets like ConceptNet and WordNet which uses English vocabulary like nouns, verbs, adjectives, adverbs to form common meanings and relations. Sometimes the linguistics vocabulary is not present or not clear e.g., examining a patient electronic medical records or physician’s handwritten notes will reveal several terminologies which are only specific to medical professionals in their field. Similarly, when the intended target is an opinion or a subjective state which may or may not be true and represent the author personal views, biases, or prejudices. Instances like these make it difficult to establish a meaningful relation for data analysis purposes. In that case, need arises to develop a database from the ground up for the semantic network to be established. This paper briefly discusses the major semantic network datasets which are open source and available for semantic analysis.
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Trovati, M., Awan, S. (2022). Semantic Network: A Brief Review of its Datasets. In: Barolli, L., Miwa, H. (eds) Advances in Intelligent Networking and Collaborative Systems. INCoS 2022. Lecture Notes in Networks and Systems, vol 527. Springer, Cham. https://doi.org/10.1007/978-3-031-14627-5_21
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