Questions tagged [topic-models]

A topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents.

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Choosing Gensim- Phrases parameters

I'm using the gensim.models.phrases in order to find bigrams in my data. For what I know,the main hyperparameters are: min_count and threshold. I have found ...
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11 views

Use mutual information score on multi label problem

I have a dataset in which each observation is assigned multiple topics, which also have a probability / confidence metric. I would like to evaluate my topic model using not just the top 1 assigned ...
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Auto scoring sales calls

I am not a statistician so pardon any incorrect technical term usage. I have learned just enough to know I don't know anything but am trying to understand the problem before engaging a real life ...
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9 views

Updating an unsupervised model but retaining similarity

In my example I am using topic modelling (specifically a version of LDA) although I think avenues for exploring this could relate to other unsupervised techniques like clustering. I train a model and ...
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30 views

Is there a way to get the optimal cutoff points based on probability of topic models and the outcomes?

I have topic models probability obtained using LDA topic models method. I’d like to use these probabilities for 5 topics to predict an ...
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7 views

Can you restrict the terms Latent Dirichlet Allocation(LDA) uses in specific topics?

I admit I do not have the full understanding of the inner-working of Latent-Dirichlet Allocation(LDA) yet. I have used the sklearn implementation on my text corpus. ...
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Predicting links between documents with topic models

I hope this is the right forum for this sort of question: I am trying to find a topic model that allows me to predict links between documents. Basically, I am trying to figure out if the topics in my ...
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Topic modelling when the “documents” are not static and new tokens are generated regularly

This question is related to this one and this one. As background, I'm working with Magic: the Gathering decklist data; I'm trying to automatically classify decks into different archetypes based on the ...
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Sentiment about topics (defined by LDA)

For a project I do a research about topics in online reviews, and the effect of these topics on the rating (by doing a regression). Furthermore and the reason I would like to have your help: I would ...
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21 views

Specify some words are not important and some words are extra important in topic modelling

I am using Latent Dirichlet Allocation in sklearn to model topics. I have a list of words that are likely to inform topics and a list of words that are not important (like stop words). Is there a way ...
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18 views

How does structural topic modeling's estimateEffect works?

I've been searching this for a while but haven't been able to find any information regarding how the STM's estimateEffect works. I'm reading the stm package ...
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Deriving Hyperparameter updates in Online Interactive Collaborative Filtering

I've been going through "Online Interactive Collaborative Filtering Using Multi-Armed Bandit with Dependent Arms" by Wang et al. and am unable to understand how the update equations for the ...
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Inference on Author model

The Author Model is an LDA based model that first time introduced in paper [The Author-Topic Model for Authors and Documents]. I have studied the inference of the LDA model and know how to obtain the ...
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Are 1-tailed 2-sample t tests suitable to assess if external validity performance is statistically significant better than a random model?

Some context: I currently have two groups of 50 text documents. Each group is about a different subject and curated by people. As such, I assume the two groups to be my ground truth. I mix the two ...
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23 views

parameter estimation on the LDA model

I have a problem with estimating the parameters of $\theta$, and $\phi$ in the Latent Dirichlet Allocation (LDA) model. The article Finding scientific topics has done the estimation of the parameters ...
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29 views

Can Latent Dirichlet Allocation (LDA) be used to generate word embeddings?

In the original Word2Vec paper (Efficient Estimation of Word Representations in Vector Space, Mikolov et al. 2013), I came across this phrase: Many different types of models were proposed for ...
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Interpreting the output of ldatuning and selecting the number of topics

I am conducting topic analysis using LDA and prior to specifying the topics, I wanted to determine the optimal number of topics statistically. I found the implementation in ldatuning to be very ...
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how would i find number of subtopic inside parent topic dynamically?

Here my objective is to create hierarchy of topic in such a way that sub topics for particular supertopic should represent the same context while it(subtopic) should be isolated with other children of ...
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8 views

Using individual documents for structural topic model or joining together small documents?

There has been a couple of other related questions about this posted but nothing exact. I'm using a structural topic model to model Twitter data (~5m tweets), the bulk of which were written in an 18m ...
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Thematic clustering of text

Please advise on starting points, research (papers,frameworks) related to thematic clustering of text. In particular on a system with two levels of clustering where second level has a temporal nature. ...
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Topic modeling/clustering using TF-IDF when adding real-time data

I’m clustering a collection of text documents (e.g., tweets) that are posted in a period of time, let’s say from a to b where <...
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Can I use LDA with 1 topic? I clustered my documents using doc2vec then DBSCAN. How can I visualize the topic of each cluster?

I did a doc2vec model then clustered the results using DBSCAN. Now that I have satisfactory results, how can I take these clusters into topics? Should i run LDA on each and make it give out 1 topic? ...
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Why in Latent Dirichlet Allocation perplexity is always best with maximum amount of topics?

I've build a Latent Dirichlet Allocation (LDA) model on 37,500 documents using the Java Mallet API. To automatically determine the "best" number of topics, I calculate the perplexity by splitting the ...
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How do you estimate α parameter of a Dynamic topic model?

Blei dynamic topic model paper suggests that it is possible to conjointly estimate \alpha and \beta in a dynamic topic model. In the paper they mention the following: "For clarity of presentation, ...
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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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28 views

Hierarchical LDA (HLDA) topics hierarchy tree level?

What are the meanings of Hlda topics tree hierarchies? Tree has different height level like level 1, 2 and 3. What are the meanings of these level? Which level shows accurate results?
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39 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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29 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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Why is my correlation matrix dropping that many NA?

I am trying to build a correlation matrix among documents per topic on a Latent Dirichlet Allocation model by text2vec, getting a doc_topic_distr matrix like below, with only first 5 documents, it's a ...
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39 views

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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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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335 views

what does negative coherence score means?

I am working on topic modeling and when I tried to see the coherence of the topics all are negative. Does anyone know what could be the interpretation behind negative score? This is the example of ...
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59 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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230 views

LDA/NMF Topic Modeling vs Topic Modeling using “skip gram” approach

I am having a little friendly debate with my coworker on how to properly/optimally do topic modeling. I am just using the regular traditional nmf/lda approach and he decided to do it using "skip grams"...
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Can NMF assign probabilities to the topics it outputs?

It's my understanding that only LDA can assign probabilities to words within each topic that it discovers since it's a probabilistic graphical model politicians 0.05 united states 0.10 obama 0.20 ...
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111 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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36 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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352 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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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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342 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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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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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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85 views

Summary statitics to describe topic x term distribution in NLP

I created a topic model which outputted 11 topics out of 437 terms on ~60000 small documents. I wanted to show how good each topic is. But I don't know what "good" means in this case. Here's the ...
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Ideas for fixing manual misclassification

Imagine the following problem. Mechanics fix cars and use a set of parts which is recorded on invoices. They also write down a classification of the work that was done from a fixed set of possible ...
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How to understand pLSA model Q function?

I know in EM algorithm M-step, it tries to solve $$ \operatorname{argmax}_{\theta} Q(\theta, \theta^{ \text{old}}) = \sum_z p(z|x; \theta^{ \text{old}}) \log p(x,z; \theta) $$ I also understand the ...
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1k 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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613 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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179 views

Perplexity calculation in variational neural topic models

I'm looking at this 2016 paper from Miao et al. https://arxiv.org/abs/1511.06038 where they use a variational autoencoder for topic modelling. To evaluate the effectiveness of their model, they use ...
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2k 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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70 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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