Exploring Redditors’ Topics with Natural Language Processing

[EN] This paper examines how people in Reddit develop topics across threads in a given subreddit and how discussions concentrate on the topic in given threads with natural language processing (NLP) methods. By implementing an LDA topic model and TF-IDF models, this paper discovers people’s aggregate...

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Detalles Bibliográficos
Autor: Zhao, Yilang
Tipo de recurso: capítulo de libro
Fecha de publicación:2022
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/189456
Acceso en línea:https://riunet.upv.es/handle/10251/189456
Access Level:acceso abierto
Palabra clave:Reddit
Online discussion community
Online discussion topics
Natural language processing
LDA
TF-IDF
Descripción
Sumario:[EN] This paper examines how people in Reddit develop topics across threads in a given subreddit and how discussions concentrate on the topic in given threads with natural language processing (NLP) methods. By implementing an LDA topic model and TF-IDF models, this paper discovers people’s aggregated concerns are related to real-world issues and their discussions are concentrative considering the topics they discuss.