Questions tagged [latent-dirichlet-alloc]

Latent Dirichlet Allocation (LDA) is an unsupervised, statistical approach to document modeling that discovers latent semantic topics in large collections of text.

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Inference for two-level Latent Dirichlet Allocation model proposed in the original paper

In the 2003 paper by Blei et. al. "Latent Dirichlet Allocation", in section 3.2, "A continuous mixture of unigrams", they propose a two-level LDA model by "marginalizing over the hidden topic variable ...
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11 views

What does each graph cuadrant means with LDA vis plot from R?

I am speeking about this graph, that shows a big probability mass. This is the way that it finally shows with some data I found online and used to understand Latent Dirichlet Allocation topic ...
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10 views

Inference on Dirichlet hyper-parameter

I'm working on a Gibbs sampler for a (somewhat custom version of) Latent Dirichlet Allocation model. In short, I have data that comes from a $K$-dimensional Dirichlet-Multinomial distribution, i.e. $$...
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7 views

Topic modelling on only 24 documents gives the same “topic” for any K

Description: I have 24 documents, each one of around 2.5K tokens. They are public speeches. My text preprocessing pipeline is a generic one, including punctuation removal, expansion of English ...
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6 views

LDA alpha equivalent in structural topic model

I'm using an implementation of the structural topic model (stm), written in R using the stm package. I want to reduce the number of topics that are prevalent in ...
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23 views

Considering the Sentiment rather than the topic in lDA model

I have a question about the lDA model, what if I consider sentiment rather than topic in this model? In this way, will the model classify the documents by sentiment? I have tested it, but it not work.
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How to intuitively interpret of topic distributions/coefficients in topic modeling

I know topic modeling such as LDA can provide the distribution of topics in documents, and the distribution of topics represent the important of that topic. However, I'm having a hard time intuitively ...
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6 views

Overlapping meaning with lda_model$plot()

I'm doing Latent Dirichlet Allocation with text2vec and end up with lda_model$plot() visualization from LDAvis package but I don't specifically understand what is the overlapping meaning with it. I ...
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13 views

Does it make sense to apply Latent Dirichlet Allocantion on topic outcomes from the model?

What I mean is that if it makes sense to apply LDA twice, the first time as it is supossed to and the second apllying the model to each topic outcome from the first application? If it is possible, ...
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10 views

Difference lemmatizing/stemming when preprocessing text to organize abstracts looking for document insights?

I'm working with R text2vec in order to apply an LDA on a 230k text data that I have on hand. I tried both stemming and lemmatizing separately but I am not completely aware of which gives out the ...
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210 views

A Bernoulli mixture model with a Dirichlet prior on the parameters

Let's $x_1,...,x_N$ be a set of observation coming from the following generative process: $$ \boldsymbol{\theta} \sim \text{Dirichlet}(\boldsymbol{\alpha})\qquad\boldsymbol{\theta},\boldsymbol\alpha\...
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28 views

Topic Modeling: How many documents “belong” to a topic?

A frequent question that arises when I present results of topic modeling to novices is: "How many documents belong to topic x?". As topic modeling is probabilistic, I hesitate giving absolute ...
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46 views

posterior predictive distribution for latent dirichlet allocation model

I want to obtain posterior predictive distribution on the LDA model, actually, I want to predict n next sample ( words in this model). can anyone help me? I attach the LDA model here, and it is ...
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17 views

Understanding the inference procedure used in Latent Dirichlet Allocation

I am trying to get a high-level understanding of the inference and parameter estimation procedure of the original Latent Dirichlet Allocation (LDA) paper. Since I'm not too familiar with Bayesian ...
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1answer
36 views

Inference of the collapsed Gibbs sampling for LDA

I am trying to understand the inference procedure of collapsed Gibbs sampling for LDA model. I refer to this document and LDA wiki page. I cannot figure out how does it simplify the sample equation ...
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24 views

How to interpret the difference in topic proportion (theta / document-topic-probability) of two groups?

I am comparing the difference in mean topic proportion (theta / document-topic-probability) of two groups. How can I interpret whether the differences are small or large, as topic proportions depend ...
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9 views

Stop words selection in topic modelling

I am doing topic modelling in below corpus having 5 documents only with pre defined two topics initially, bank and restaurant. First two documents are about bank and 3rd and 4th documents are about ...
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71 views

Custom topic priors in LDA

I've been working with LDA (Latent Dirichlet Allocation topic model) for a while now and I believe I have an intermediate understanding of it. The unsupervised nature of LDA is one of its big ...
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421 views

gensim LdaModel - How to reduce the number of words in each topic?

I'm trying to get more sparse topics (Less overlaps between different topics). https://radimrehurek.com/gensim/models/ldamodel.html I know it should be determined by the alpha parameter. I've ...
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21 views

LDA: weight distributions of inferred documents

I have trained a two-topic Latent Dirichlet Allocation (LDA) model on a corpus and I am now inferring on a test corpus (the nature of the corpus is irrelevant). During inference, for each new document ...
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14 views

how to perform statistical analysis on topics produced by topic models?

I have a large corpus of over 1.2 million text documents. After applying LDA to a small sample of the corpus, I have determined the number of topics be 34 using topic coherence score. Here, some ...
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1answer
48 views

using latent dirichlet allocation to reduce the number of dimensions in bag of words model?

Does anyone have experience reducing the dimensions in a traditional bag of words model? For example, if you want to train a decision tree on a large set of reviews, the size of the vocabulary ...
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28 views

Prerequisites for Latent Dirichlet Allocation

I have read several "intuitive" introductions to LDA. However, I now want to learn it properly. I have already read through most of Duda, and that was my introduction to data science. However, I ...
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151 views

LDA detect new emerging topics

Thanks for stopping by. I have a directional question - I've built a Latent Dirichlet Allocation using Gensims Mallet wrapper. I trained the model once on OldDataSet.csv and measured coherence. I have ...
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1k views

What is the formula for c_v coherence?

I've recently been playing around with Gensim LDAModel. I use coherence to evaluate the results. Gensim offers a few coherence measures. This includes c_v and ...
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178 views

Choosing the number of topics in topic modeling with multiple “elbows” in the coherence plot

When plotting the number of topics on the x-axis and the coherence score on the y-axis, I had expected to see an "elbow" (for example, here and here). In this case, however, the plot does not have a ...
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64 views

Visualizing a Latent Dirichlet Allocation (LDA) by Multidimensional Scaling (MDS)

I did an LDA with four topics for four different Smartphones. This was done using customer Reviews of Amazon. ...
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46 views

How to interpret LDA (Latent Dirichlet Allocation)?

Say I want to run topic modeling with LDA on The 20 newsgroups text dataset. So basically a dataset with texts where every text belongs to one of 20 categories. I want the LDA to split the documents ...
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45 views

When DV is dichotomous and IV is ordinal, should I use LPA or LCA?

Suppose my dependent/outcome variable is composed of 6 vignettes that has dichotomous outcomes of "Yes" (1) or "No" (0). Normally, I can just get a sum-score total so that it's a score from 0 (...
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51 views

Why does perplexity change with different ranges of k?

I ran a 5-fold cross-validation in R to calculate LDA perplexity for k = 2:9 using a 10% sample of my data. The output was: ...
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12 views

Why do topics found by latent dirichlet allocation correlate negatively?

I am dealing with 14000 documents that I am trying to analyze with an LDA. Also I am trying to interpret the outcome. I notice negative correlations between the topic probabilities. I think I expected ...
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39 views

Combining the topics of two Latent Dirichlet Allocations

How to combine two LDAs? Let's suppose we have one corpus and we have estimated two Latent Dirichlet Allocations for two sub-corpuses : one for sub corpus A and another for sub corpus B. Now first ...
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72 views

Question about the generative process in latent Dirichlet allocation (LDA)?

According to the wikipedia article about LDA https://en.wikipedia.org/wiki/Latent_Dirichlet_allocation in the "Generative process" section: Isn't this a contradiction? As you know "~" symbol means "...
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699 views

LDA: find percentage / number of documents per topic

I'm using LDA to find topics in a corpus. Everything works fine (I have the topics). But I would like to have the percentage / number of documents in each topic. It's possible? I looked at scikit-...
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302 views

How do I compute LDA topic similarity? [closed]

I am using the tidytext, quanteda, and tm packages in R to analyse my corpus of 220 documents. Using the topicmodels package I have extracted key topics using LDA. I now have a tidy dataframe that ...
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1answer
773 views

Assign sentences to their respective topics using LDA

Is there a way to find out what sentences fall under which topic detected using Latent Dirichlet Allocation (LDA)? Assume I have already used LDA to extract topics. Now I want to determine which ...
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1answer
1k views

Seeded LDA using topicmodels in R

I would like to perform a LDA in R by means of topicmodels. To make the resulting topics better match the topics I want to see, I would like to input "seed words" for these topics into the LDA, ...
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1answer
50 views

How to see the words shared across topics in LDA model?

I am trying to find the words that are shared across the topics and words unique to a topic using LDA model in R. Is there any package or function? Thanks
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1answer
232 views

How to implement topic modelling in regression analysis

I have a dataset consisting of hotel reviews, ratings, and other features such as traveller type, and word count of the review. I want to perform topic modeling (LDA) and use the topics derived from ...
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8k views

How does topic coherence score in LDA intuitively makes sense ?

referring to: http://qpleple.com/topic-coherence-to-evaluate-topic-models/ In order to decide the optimum number of topics to be extracted using LDA, topic coherence score is always used to measure ...
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38 views

Definition of distribution conditioned on both a categorical and Dirichlet prior

If we have a conditional categorical distribution, with unknown parameters, we can represent with a table, as in the example below: \begin{align*} &z \quad P(z|\theta)\\ &0 \quad \theta_0\\ &...
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1answer
336 views

Assess the dependence of LDA on the random seed

New to latent Dirichlet Allocation (LDA), I would like to be sure that my output (in the first the step, the word-per-topic probabilities) depends on the input merely, and is (somewhat) stable ...
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51 views

Recovering $\theta$ in Dirichlet-Multinomial (Polya) distribution

I'm working on Latent Dirichlet Allocation with Collapsed Gibbs Sampling. LDA has two Dirichlet-Multinomial distribution and one of them is a document-topic distribution that determines the ...
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20 views

Evaluating accuracy of the classifier based on sample?

I have a rather odd question which unfortunately goes beyond my knowledge of stats so any advice will be much appreciated. We built a clustering model on the text data (LDA) and then assigned classes ...
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1answer
358 views

Can I use word2vec vectors as input features to NMF or LDA?

I'm trying to do some topic modelling on my corpus and I want to use Word2Vec vectors as an input to my NMF and LDA models. How do I do this? Is it even possible?
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1answer
2k views

LDA and test data perplexity [closed]

I've performed Latent Dirichlet Analysis on a training set of documents. At the ideal number of topics I would expect a minimum of perplexity for the test dataset. However, I find that the ...
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1answer
18 views

What ML architectures might be best to classify text as containing an event or not?

I was looking for some ML/NLP advice. I have 50,000 newsletters (emails) that are labelled either “event” or “not event”. Here is an example of each: Not event: ...
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263 views

LDA implementaion in pymc3

I am implementing LDA with pymc3 using the referred code for pymc from the post Latent Dirichlet Allocation in PyMC I am trying to use it for pymc3 bt having problems defining ...
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1answer
165 views

Joint distribution in latent Dirichlet model

Given the graphical model of LDA (latent Dirichlet model) We have the factorization of the joint distribution $$P = \prod_{d = 1}^{D}P(\theta_{d}|\alpha)\prod_{n = 1}^{N}P(z_{d, n}|\theta_d)P(w_{d, ...
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1answer
81 views

Generalized Additive Model for timely trends of topics generated via Latent Dirichlet Allocation?

I am conducting a topic modeling study via Latent Dirichlet Allocation (LDA) on scientifc abstracts over a range of about 20 years (in R). One of the outputs of LDA is a document-topic-distribution ...