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  1. 1041
    “…Additionally, a latent Dirichlet allocation (LDA) probabilistic topic modeling method was applied to review the entire data set using a semiautomatic approach. …”
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    Online Artículo Texto
    Using Large-scale Social Media Analytics to Understand Patient Perspectives About Urinary Tract Infections: Thematic Analysis
  2. 1042
    “…MetaDecoder was built as a two-layer model with the first layer being a GPU-based modified Dirichlet process Gaussian mixture model (DPGMM), which controls the weight of each DPGMM cluster to avoid over-segmentation by dynamically dissolving contigs in small clusters and reassigning them to the remaining clusters. …”
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    MetaDecoder: a novel method for clustering metagenomic contigs
  3. 1043
    “…Correlations between sentiments and the daily infection, death, and vaccination cases were calculated. The latent dirichlet allocation model was applied to identify topics of negative tweets from the beginning of vaccination. …”
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    Online Artículo Texto
    Public Opinion and Sentiment Before and at the Beginning of COVID-19 Vaccinations in Japan: Twitter Analysis
  4. 1044
    “…The interviews were analyzed using the traditional qualitative, hermeneutic phenomenology method as well as latent Dirichlet allocation (LDA), an unsupervised machine learning method clustering words from documents into topics. …”
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    Experiences of Siblings of Children With Neurodevelopmental Disorders: Comparing Qualitative Analysis and Machine Learning to Study Narratives
  5. 1045
    “…METHODS: Topic model analysis with latent Dirichlet allocation (LDA) identified themes in US tweets with the term “quit smoking.” …”
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    COVID-19 and Tweets About Quitting Cigarette Smoking: Topic Model Analysis of Twitter Posts 2018-2020
  6. 1046
    “…Subsequently, two independent investigators analyzed posts qualitatively to define their authors’ interests, profile characteristics, content type, and sentiment. Latent Dirichlet allocation analysis topic modeling was then applied to find salient terms and topics related to false or misleading content, and their similarity was calculated through an intertopic distance map. …”
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    Characterization of False or Misleading Fluoride Content on Instagram: Infodemiology Study
  7. 1047
    por Leung, Yue Tong, Khalvati, Farzad
    Publicado 2022
    “…METHODS: We obtained a data set of 9266 Reddit posts from the subreddit \rCOVID19_support, from February 14, 2020, to July 19, 2021. We used the latent Dirichlet allocation (LDA) topic model to identify the topics that were mentioned on the subreddit and analyzed the trends in the prevalence of the topics. …”
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    Exploring COVID-19–Related Stressors: Topic Modeling Study
  8. 1048
    “…In Python, topics were modeled by latent Dirichlet allocation. Rule-based sentiment analysis scored interactions by emotional valence. …”
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    Online Artículo Texto
    Integrating Natural Language Processing and Interpretive Thematic Analyses to Gain Human-Centered Design Insights on HIV Mobile Health: Proof-of-Concept Analysis
  9. 1049
    “…Latent Dirichlet Allocation (LDA) is an approach to unsupervised learning that aims to investigate the semantics among words in a document as well as the influence of a subject on a word. …”
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    Weighted Joint Sentiment-Topic Model for Sentiment Analysis Compared to ALGA: Adaptive Lexicon Learning Using Genetic Algorithm
  10. 1050
    por Hu, Mengke, Conway, Mike
    Publicado 2022
    “…METHODS: We utilized a topic modeling natural language processing method (more specifically latent Dirichlet allocation). Topic modeling is a popular unsupervised learning technique that can be used to automatically infer topics (ie, semantically related categories) from a large corpus of text. …”
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    Perspectives of the COVID-19 Pandemic on Reddit: Comparative Natural Language Processing Study of the United States, the United Kingdom, Canada, and Australia
  11. 1051
    “…Topic modeling using the LDA (Latent Dirichlet Allocation) method and emotion analysis were conducted to analyze the posts from Weibo, China’s primary social media platform. …”
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    Topical and emotional expressions regarding extreme weather disasters on social media: a comparison of posts from official media and the public
  12. 1052
    “…Topic modelling was done with Latent Dirichlet Allocation and visualized with Multidimensional scaling. …”
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    Sentiment analysis of COVID-19 tweets from selected hashtags in Nigeria using VADER and Text Blob analyser
  13. 1053
    por Churchill, Rob, Singh, Lisa
    Publicado 2023
    “…We show the effectiveness of this approach using Latent Dirichlet Allocation (LDA), and demonstrate the ability of TND to improve the quality of LDA topics in noisy document collections. …”
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    Online Artículo Texto
    Using topic-noise models to generate domain-specific topics across data sources
  14. 1054
    por Wu, Nemin, Mu, Lan
    Publicado 2023
    “…We performed a topic modeling analysis using the Latent Dirichlet Allocation (LDA), and verified that most of the collected tweets were related to grocery-shopping demands or experiences. …”
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    Online Artículo Texto
    Impact of COVID-19 on online grocery shopping discussion and behavior reflected from Google Trends and geotagged tweets
  15. 1055
    “…Topic modeling using latent Dirichlet allocation (LDA) was used to examine major topics discussed in water pipe–related posts before and during the pandemic. …”
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    Potential Impact of the COVID-19 Pandemic on Public Perception of Water Pipes on Reddit: Observational Study
  16. 1056
    “…This case study employed Latent Dirichlet Allocation (LDA) topic modeling, Bidirectional Encoder Representations from Transformers (BERT) emotion analysis, and human textual analysis and examined 180,128 tweets scraped by Twitter Application Programming Interface’s (API) keyword function from January 2020 to June 2021. …”
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    A case study of using natural language processing to extract consumer insights from tweets in American cities for public health crises
  17. 1057
    “…We used natural language processing and the Latent Dirichlet Allocation to analyse the qualitative experiences of the participants as well as descriptive statistics and multiple logistic regression to determine factors influencing postgraduate educational readiness. …”
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    Educational readiness among health professionals in rheumatology: low awareness of EULAR offerings and unfamiliarity with the course content as major barriers—results of a EULAR-funded European survey
  18. 1058
    “…The remaining references were then ranked for relevance using an algorithm that considers term frequency and latent Dirichlet allocation (LDA) topic modeling. This ranking was evaluated with respect to (1) the number of studies screened in order to identify 95 % of known relevant studies and (2) the “Work Saved over Sampling” (WSS) performance metric. …”
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    SWIFT-Review: a text-mining workbench for systematic review
  19. 1059
    “…METHODS: A topic model was computed for all posts (N = 131,004) in the ISG BlueBoard using Latent Dirichlet Allocation. A model containing 25 topics was selected on the basis of intelligibility as determined by diagnostic metrics and qualitative investigation. …”
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    What’s all the talk about? Topic modelling in a mental health Internet support group
  20. 1060
    “…For each participant, the total content of Facebook posts was extracted. Using the latent Dirichlet allocation natural language processing technique, Facebook language topics were correlated with frequency of Facebook use. …”
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    Variations in Facebook Posting Patterns Across Validated Patient Health Conditions: A Prospective Cohort Study
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