Topic modeling algorithms and applications: A survey
Topic modeling is used in information retrieval to infer the hidden themes in a collection of
documents and thus provides an automatic means to organize, understand and summarize …
documents and thus provides an automatic means to organize, understand and summarize …
BERTopic: Neural topic modeling with a class-based TF-IDF procedure
M Grootendorst - ar** review
Background Topic modeling approaches allow researchers to analyze and represent written
texts. One of the commonly used approaches in psychology is latent Dirichlet allocation …
texts. One of the commonly used approaches in psychology is latent Dirichlet allocation …
A survey on neural topic models: methods, applications, and challenges
Topic models have been prevalent for decades to discover latent topics and infer topic
proportions of documents in an unsupervised fashion. They have been widely used in …
proportions of documents in an unsupervised fashion. They have been widely used in …
The role of textual analysis in oil futures price forecasting based on machine learning approach
X Gong, K Guan, Q Chen - Journal of Futures Markets, 2022 - Wiley Online Library
This paper offers an innovative approach to capture the trend of oil futures prices based on
the text‐based news. By adopting natural language processing techniques, the text features …
the text‐based news. By adopting natural language processing techniques, the text features …
The search for solid ground in text as data: A systematic review of validation practices and practical recommendations for validation
Communication research frequently applies computational text analysis methods (CTAM) to
detect and measure social science constructs. However, the validity of these measures can …
detect and measure social science constructs. However, the validity of these measures can …