“…In this study, we used the latent Dirichlet allocation (LDA) topic model and sentiment analysis to explore public reactions to the COVID-19 vaccine. …”
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“…The calculations of the eigenvalue equation have been implemented considering both the Dirichlet conditions (zero flux) and the open boundary conditions (non-zero flux) in the planes perpendicular to the direction of the applied electric field, which guarantees the validity of the results presented in this study for quasi-steady states with extremely high lifetimes. …”
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“…Networks of countries, research disciplines, and most frequently used terms were visualized. The Latent Dirichlet Allocation method was used for topic modeling. …”
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“…The application of the Dynamic Latent Dirichlet Allocation (DLDA) model revealed three fundamental topics, which remained stable over time: vaccination plan info, usefulness of vaccinating and concerns about vaccines (risks, side effects and safety). …”
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“…Based on multi-source heterogeneous data, combined with the latent Dirichlet allocation topic model, social network analysis, and econometric methods, this paper explores whether individual purchase decisions and company-level cooperative research and development will promote the promotion of new energy vehicles. …”
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“…This paper analyzes and provides a comparison of the performance of Latent Dirichlet Allocation (LDA), Dynamic Topic Model (DTM), and Embedded Topic Model (ETM) techniques. …”
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“…Our findings showcase that 50 initially retrieved topics are narrowed down to just 4, when combining Latent Dirichlet Allocation with ARM. Our methodology facilitates producing more accurate and generalizable results, whilst exposing implications regarding social media user attitudes.…”
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“…During external evaluations, researchers’ publications were clustered using Dirichlet Process Mixture Model (DPMM), recommended grants by our model were then aggregated per cluster through Recency Weight, and finally researchers were invited to provide ratings to recommendations to calculate Precision@k. …”
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“…This work developed an approach based on complex Green functions (solving the arbitrary Dirichlet and Neumann boundary problem) which matches measurements with unprecedented accuracy. …”
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“…Bioinformatics analysis was performed, and a machine learning-based Latent Dirichlet Allocation (LDA) model was used to identify the subfield research topics. …”
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“…The data were collected through the crawler code, and latent Dirichlet allocation (LDA) and grounded theory were used to mine the theme features after data cleaning. …”
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“…Topic modeling through Latent Dirichlet Allocation identifies the topics of discussion in Tweets, which this study uses to induce a directed multilayer network wherein users (in one layer) are connected to the conversations and topics (in a second layer) in which they have participated, with inter-layer connections representing user participation in conversations. …”
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“…Then, we thematically classified the tweets and obtained a subset of tweets related to health and nutrition. We used a Dirichlet regression to compare the thematic segmentations of the two groups. …”
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“…We developed an innovative statistical and computational approach using a Latent Dirichlet Allocation (LDA) model that extends the concept of topic modeling used in text mining. …”
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“…To discover main topics embedded in data science discussions, we used latent Dirichlet allocation (LDA), a probabilistic approach for topic modeling. …”
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“…A U-Net was used to classify the low-dose projections into “risk classes” in simulated breasts with soft-tissue lesions; class probabilities were modified using post hoc Dirichlet calibration (DC). DC improved the multiclass segmentation (Dice = 0.43 vs. 0.28 before DC) and significantly reduced false positives (FPs) from the class of the highest risk of masking (sensitivity = 81.3% at 2 FPs per image vs. 76.0%). …”
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“…This paper collected data from 747 doctors and 105 032 reviews from WeDoctor, one of China’s most popular OHCs, in 2019. We employed Latent Dirichlet Allocation topic modeling to extract 3 topics and analyzed their effects on patient e-doctor choice using a multiple regression method. …”
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“…The statistical population is all COVID-19 publications from PubMed Central® (PMC), extracted from November 2019 to June 2021. Latent Dirichlet allocation (LDA) was used for clustering, and support vector machine (SVM), scikit-learn library, and Python programming language were used for text classification. …”
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“…We conducted a case-control study involving 410 Han Chinese individuals, using exploratory structural equation modeling to identify two dietary patterns, and a Dirichlet multinomial mixture model to classify 250 colorectal neoplasm cases into three gut microbiota enterotypes. …”
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