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Short Text Topic Modeling: Application to tweets about Bitcoin
March 17, 2022 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Hugo Schnoering
arXiv ID
2203.11152
Category
cs.IR: Information Retrieval
Cross-listed
cs.LG
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Understanding the semantic of a collection of texts is a challenging task. Topic models are probabilistic models that aims at extracting "topics" from a corpus of documents. This task is particularly difficult when the corpus is composed of short texts, such as posts on social networks. Following several previous research papers, we explore in this paper a set of collected tweets about bitcoin. In this work, we train three topic models and evaluate their output with several scores. We also propose a concrete application of the extracted topics.
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