Article: Detecting Favorite Topics in Computing Scientific Literature via Dynamic Topic Modeling
type: Nanopublication
has assertion: assertion
has provenance: provenance
has publication info: pubinfo
created: 2023-11-22T19:26:28.402Z
creator: Rosa Virginia Encinas Quille
license: https://creativecommons.org/licenses/by/4.0/
has nanopub type: ScholarlyWork
introduces: Detecting Favorite Topics in Computing Scientific Literature via Dynamic Topic Modeling

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has algorithm: RSA

Detecting Favorite Topics in Computing Scientific Literature via Dynamic Topic Modeling
type: ResearchPaper
abstract: Topic modeling comprises a set of machine learning algorithms that allow topics to be extracted from a collection of documents. These algorithms have been widely used in many areas, such as identifying dominant topics in scientific research. However, works addressing such problems focus on identifying static topics, providing snapshots that cannot show how those topics evolve. Aiming to close this gap, in this article, we describe an approach for dynamic article set analysis and classification. This is accomplished by querying open data of notable scientific databases via representational state transfers. After that, we enforce data management practices with a dynamic topic modeling approach on the associated metadata available. As a result, we identify research trends for a given field at specific instants and the referred terminology trends evolution throughout the years. It was possible to detect the associated lexical variation over time in published content, ultimately determining the so-called “hot topics” in arbitrary instants and how they correlate.
date: 2023
is part of: IEEE Access
authored by: Márcio Barbado Júnior
authored by: Rosa Virginia Encinas Quille
authored by: Pedro Luiz Pizzigatti Corrêa
authored by: Felipe Valencia De Almeida
authored by: José Meléndez Barros

Márcio Barbado Júnior
type: Person
affiliation: University of São Paulo

Rosa Virginia Encinas Quille
type: Person
affiliation: University of São Paulo

Pedro Luiz Pizzigatti Corrêa
type: Person
affiliation: University of São Paulo

Felipe Valencia De Almeida
type: Person
affiliation: University of São Paulo

José Meléndez Barros
type: Person
affiliation: University of São Paulo

University of São Paulo
type: Organization