A clustering-based topic model using word networks and word embeddings

A clustering-based topic model using word networks and word embeddings

Abstract Online social networking services like Twitter are frequently used for discussions on numerous topics of interest, which range from mainstream and popular topics (e.g., music and movies) to niche and specialized topics (e.g., politics). Due to the popularity of such services, it is a challe...

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Bibliographic Details
Main Authors: Wenchuan Mu, Kwan Hui Lim, Junhua Liu, Shanika Karunasekera, Lucia Falzon, Aaron Harwood
Format: Article
Language:English
Published: SpringerOpen 2022-04-01
Series:Journal of Big Data
Subjects:
Topic modelling
Clustering
Word embedding
Twitter
Microblogs
Social networks
Online Access:https://doi.org/10.1186/s40537-022-00585-4

Internet

https://doi.org/10.1186/s40537-022-00585-4

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