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 …
The evolution of topic modeling
R Churchill, L Singh - ACM Computing Surveys, 2022 - dl.acm.org
Topic models have been applied to everything from books to newspapers to social media
posts in an effort to identify the most prevalent themes of a text corpus. We provide an in …
posts in an effort to identify the most prevalent themes of a text corpus. We provide an in …
Virtually in this together–how web-conferencing systems enabled a new virtual togetherness during the COVID-19 crisis
Regulations to contain the spread of COVID-19 have affected corporations, institutions, and
individuals to a degree that most people have never seen before. Information systems …
individuals to a degree that most people have never seen before. Information systems …
Topic modeling using latent Dirichlet allocation: A survey
We are not able to deal with a mammoth text corpus without summarizing them into a
relatively small subset. A computational tool is extremely needed to understand such a …
relatively small subset. A computational tool is extremely needed to understand such a …
Topic modeling in embedding spaces
Topic modeling analyzes documents to learn meaningful patterns of words. However,
existing topic models fail to learn interpretable topics when working with large and heavy …
existing topic models fail to learn interpretable topics when working with large and heavy …
Can large language models transform computational social science?
Large language models (LLMs) are capable of successfully performing many language
processing tasks zero-shot (without training data). If zero-shot LLMs can also reliably classify …
processing tasks zero-shot (without training data). If zero-shot LLMs can also reliably classify …
From “Incel” to “Saint”: Analyzing the violent worldview behind the 2018 Toronto attack
This paper combines qualitative and quantitative content analysis to map and analyze the
“Incel” worldview shared by members of a misogynistic online community ideologically …
“Incel” worldview shared by members of a misogynistic online community ideologically …
Topic modeling: a comprehensive review
Topic modelling is the new revolution in text mining. It is a statistical technique for revealing
the underlying semantic structure in large collection of documents. After analysing …
the underlying semantic structure in large collection of documents. After analysing …
Full-text or abstract? examining topic coherence scores using latent dirichlet allocation
This paper assesses topic coherence and human topic ranking of uncovered latent topics
from scientific publications when utilizing the topic model latent Dirichlet allocation (LDA) on …
from scientific publications when utilizing the topic model latent Dirichlet allocation (LDA) on …
Topic modelling meets deep neural networks: A survey
Topic modelling has been a successful technique for text analysis for almost twenty years.
When topic modelling met deep neural networks, there emerged a new and increasingly …
When topic modelling met deep neural networks, there emerged a new and increasingly …