Citation Graph Analysis and Alignment between Citation Adjacency and Themes or Topics of Publications in the Area of Disease Control through Social Network Surveillance (original) (raw)

2022

Abstract

This paper presents a Data-Network Science study on a dataset of publications archived in The Semantic Scholar Open Research Corpus (S2ORC) database and categorized under the area of “Disease Control through Social Network Surveillance,” an area abbreviated from now on as “DCSNS.” In particular, our dataset consists of 10866 documents (which are articles and reviews), retrieved through a Boolean search, published in the period from 1983, the first year of cataloguing such publications in S2ORC, to 2020. Retrieving also the corpus of abstracts of these documents (publications) and applying the standard LDA Topic Modeling technique, we found an optimal number of six topics producing the maximum topic coherence score among the corresponding topic models with varying numbers of topics. In that matter, the network of our study becomes a directed citation graph of publications in the area of DCSNS, with nodes/publications labeled by the Topics (into which Topic Modeling categorizes words ...

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