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Topic Modeling Genre: An Exploration of French Classical and Enlightenment Drama [PDF]
, 2015 The concept of literary genre is a highly complex one: not only are different genres frequently defined on several, but not necessarily the same levels of description, but consideration of genres as cognitive, social, or scholarly constructs with a rich ...
Schöch, Christof +1 more
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On a Topic Model for Sentences
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016 Probabilistic topic models are generative models that describe the content of documents by discovering the latent topics underlying them. However, the structure of the textual input, and for instance the grouping of words in coherent text spans such as sentences, contains much information which is generally lost with these models.
Georgios Balikas +2 more
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Probabilistic Topic Models [PDF]
IEEE Signal Processing Magazine, 2010 In this article, we review probabilistic topic models: graphical models that can be used to summarize a large collection of documents with a smaller number of distributions over words. Those distributions are called "topics" because, when fit to data, they capture the salient themes that run through the collection.
David M. Blei +2 more
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A Topic Coverage Approach to Evaluation of Topic Models [PDF]
IEEE Access, 2021 Topic models are widely used unsupervised models capable of learning topics - weighted lists of words and documents - from large collections of text documents. When topic models are used for discovery of topics in text collections, a question that arises naturally is how well the model-induced topics correspond to topics of interest to the analyst.
Damir Korencic +3 more
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Identify Topic Relations in Scientific Literature Using Topic Modeling
, 2020 IEEE Over the past five years, topic models have been applied to bibliometrics research as an efficient tool for discovering latent and potentially useful content.
Wang, X +7 more
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Marketing Insights from Reviews Using Topic Modeling with BERTopic and Deep Clustering Network
Applied Sciences, 2023 The feedback shared by consumers on e-commerce platforms holds immense value in marketing, as it offers insights into their opinions and preferences, which are readily accessible.
Yusung An, Hayoung Oh, Joosik Lee
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Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022 We propose a new problem called coordinated topic modeling that imitates human behavior while describing a text corpus. It considers a set of well-defined topics like the axes of a semantic space with a reference representation. It then uses the axes to model a corpus for easily understandable representation. This new task helps represent a corpus more
Pritom Saha Akash +2 more
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CoRR, 2011 Latent Dirichlet Allocation models discrete data as a mixture of discrete distributions, using Dirichlet beliefs over the mixture weights. We study a variation of this concept, in which the documents' mixture weight beliefs are replaced with squashed Gaussian distributions.
Hennig, P. +3 more
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topicmodels: An R Package for Fitting Topic Models [PDF]
, 2011 Topic models allow the probabilistic modeling of term frequency occurrences in documents. The fitted model can be used to estimate the similarity between documents as well as between a set of specified keywords using an additional layer of latent ...
Kurt Hornik +3 more
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Social Sciences, 2018 The Men’s Rights Activism (MRA) movement and its sub-movement The Red Pill (TRP), has flourished online, offering support and advice to men who feel their masculinity is being challenged by societal shifts.
J. B. Mountford
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