Visualizing Temporal Topic Embeddings with a Compass

Dynamic topic modeling is useful at discovering the development and change in latent topics over time. However, present methodology relies on algorithms that separate document and word representations. This prevents the creation of a meaningful embedding space where changes in word usage and documen...

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Vydané v:IEEE transactions on visualization and computer graphics Ročník 31; číslo 1; s. 272 - 282
Hlavní autori: Palamarchuk, Daniel, Williams, Lemara, Mayer, Brian, Danielson, Thomas, Faust, Rebecca, Deschaine, Larry, North, Chris
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States IEEE 01.01.2025
Predmet:
Cluster analysis
Clustering algorithms
Compass
Dynamic topic modeling
Electronic mail
High dimensional data
Streams
Training
Vectors
Visualization
ISSN:1077-2626, 1941-0506, 1941-0506
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Shrnutí:Dynamic topic modeling is useful at discovering the development and change in latent topics over time. However, present methodology relies on algorithms that separate document and word representations. This prevents the creation of a meaningful embedding space where changes in word usage and documents can be directly analyzed in a temporal context. This paper proposes an expansion of the compass-aligned temporal Word2Vec methodology into dynamic topic modeling. Such a method allows for the direct comparison of word and document embeddings across time in dynamic topics. This enables the creation of visualizations that incorporate temporal word embeddings within the context of documents into topic visualizations. In experiments against the current state-of-the-art, our proposed method demonstrates overall competitive performance in topic relevancy and diversity across temporal datasets of varying size. Simultaneously, it provides insightful visualizations focused on temporal word embeddings while maintaining the insights provided by global topic evolution, advancing our understanding of how topics evolve over time.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1077-2626
1941-0506
1941-0506
DOI:10.1109/TVCG.2024.3456143