Questions tagged [sentiment-analysis]
The sentiment-analysis tag has no usage guidance.
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First difference of logs of negative numbers causes trouble
I have the following problem: I have a timeseries with the prices for a few futures, which is non-stationary (according to ADF test). If I apply first difference of logs, ADF shows stationarity.
But I ...
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Sentiment Analysis with a Continuos Output Labels
Problem Setting/Context:
I have feedback(each feedback has multiple sentences) associated with different products(you can safely assume that a feedback talks about one single product), I need to ...
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struggled in result of sentiment analysis [closed]
i try to do sentiment analysis (tweet scor) after i cleaned the data successfully, i struggled in the sentiment analysis step
and i cant get the result , any help pleas
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Weigthening social media sentiment scores
I struggle to understand how to implement a logical weighting of sentiment data.
I predicted the sentiment for multiple Reddit comments. How can I weight them according to their scores? The problem is ...
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How normalized, weighted composite score measaured?
How can we convert a vector of repeated measures of a variable into one value when the vector has varying length in different instances? For instance, let's assume ...
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how many instances are needed to do a text classification?
I am currently trying to gather data for doing a text classification that determines whether the content of the text is "depressing" or not. it is going to be a binary classification.
my ...
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How to do sentiment analysis in financial news?
I already have financial news that I got from financial news sites. Now I want to apply sentiment analysis to classify news as positive, neutral, or negative. I do not know what to do. I know some ...
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How to combine two manual classifications
We are manually classifying texts as positive (+1), neutral (0) or negative (-1). The purpose is to train a sentiment analysis classifier.
We are two people, and we have both classified the same ...
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Normalization - before or after merging datasets
I'm working on a project to see if the sentiments of a book series matches that of the movie adaptations. I perform sentiment analysis and compare the results. The books contain far more words than ...
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Can a voice-based sentiment analysis model differ depending on the language?
I'm trying to figure out if building a voice-based sentiment analysis model for Brazilian portuguese would be possible. Since I couldn't find any free Brazilian datasets for voice analysis, would it ...
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Why Accuracy increase only 1% after data augmentation NLP?
i have small dataset 4840 samples (60% negative ,28% positive,12% negative) i use data augmentation on training set (70%train 30% test) and i have about 2000 samples for each class while test is ...
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What are the covariates/explanatory variables in a news sentiment model?
In "Measuring News Sentiment", a working paper by the Fed, we have the following model:.
The index $a$ indexes the news articles. A fixed effect is a term (random or not) which is allowed to ...
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Is it valid to calculate Spearman/Cramér's V with duplicate values?
I have a dataset that I want to analyze using statistic measures. Because of the nature of the data, it seems like Cramér's V is the correct method (For cases involving (school) grades only, Spearman ...
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Calculate the sentiment knowing the single probabilities
I am working on finding the sentiment of some text. Right now I am using a python library called VADER that for each sentence it gives me back the probability that a specific phrase is positive, ...
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How to parametrize a Decisiontree Classifier for NLP tasks?
I want to use sklearns DecisionTreeClassifier for sentiment analysis. I am fully aware that a decision tree is probably not a good model for this kind of task, but I want to try it anyways for the ...
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Sentiment Analysis but for Descriptions in Texts?
Reviewing literature about sentiment analysis, I can only find contributions focussing on the sentiment of the author. Famous examples are twitter posts or movie reviews. I wonder if there are ...
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How can I apply naive Bayes classifier for three classes (Positive, Negative and Neutral) in text data?
I found a naive Bayes classifier for positive sentiment or a negative sentiment Citius: A Naive-Bayes Strategy for Sentiment Analysis on English Tweets. But with most available datasets online, ...
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Accuracy, Precision, Recall RMSE and MAE values are same for SVM, Naive Bayes and Random Forest
I am studying on sentiment analysis of tourist reviews. 90% of reviews are positive the rest are negative.
My Accuracy, Precision, Recall RMSE, and MAE values are the same for SVM, Naive Bayes, and ...
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Complexity of Maximum Entropy Algorithm in Sentiment Analysis
Does anyone know how the process of calculating the complexity of the maximum entropy algorithm and its implementation later in the sentiment analysis?
Please help me, because I haven't got a ...
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Can I skip the Keras Embedding Layer if I already transformed the data to Word2Vec (Google News 300 format)?
Trying to do sentiment analysis with an LSTM NN. I think I understand what the embedding layer does: map each word to a fixed-di-vector.
However, previously, for each text sample, I transformed each ...
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How to model negative zero-inflated continuous data?
I am currently trying to apply a model (family = gaussian) to an indicator of sentiment score, values range from -4 to +2, is zero-inflated and is continuous.
I want to look whether there is a ...
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Feature Selection in Twitter Sentiment Analysis
I'm currently working on a twitter sentiment analysis project. In this project, one requirement is to perform Feature selection for a better prediction. But I'm fairly confused about the techniques to ...
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How to Find Whether There is a Difference in Proportion of Comments in Sentiment Analysis
I have two questions to solve and need your help doing this in R Studio:
I want to find whether there is a significant difference in the proportion of students (For Each Sentiment Analysis ...
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Combining two sequences for text classification
I'm doing text classification on comments posted on articles/stories. The two human-labeled classes are appropriate and not appropriate (not the same as happy/angry or any "sentiment" ...
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How do I analyze the effects of pandemic on tone of online comments?
I am looking at analyzing the effects of Covid pandemic on online communications. I am hypothesizing that user comments on discussion forums are significantly more negative in tone during the Covid ...
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NLP algorithm: sentiment with specific guidelines
So I have this situation, I have filtered a bunch of single independent sentences that I filtered because they contain the word X (in my case, X = "budget"). if the meaning of the sentence is "budget ...
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Approaches to analyzing data from forum
Working with self written example data that mimic a chat-forum with different forums (i.e. cars, politics, sports) and different threads (i.e. "why is porsche popular?", "thoughts on andrew yang?") in ...
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What method can be used to find key phrases in sentiment analysis?
I've just completed a fastai NLP processing sentiment analysis, that is, a binary classification problem using text data. It turned out very well, but I'm wondering if there is a way to find the key ...
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No Training Dataset for Sentiment Analysis Algo
I am learning about the potential with Sentiment Analysis and have gone through many examples but I am still unsure about my understanding of one crucial detail: does one always need to start ...
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R: Naive Bayes model e1071, why does it works with totally different columns in training ad testing?
I'm working with the e1071:: naiveBayes() function, but I don't figure out how it works. My doubts arose when I read this post. I've posted this question on SO, but ...
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Evaluating mediator effect, through SEM model selection with AIC [duplicate]
I am new to SEM and the lavaan R package, so perhaps this is a basic question.
I have social media data with three variables:
...
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Correlation between sentiment opinions of articles and sentiment of tweets. Comment on appropriate method [closed]
I want to measure a set of hashtags on twitter, and see if peoples sentiment on a set of hashtags is affected by the sentiment of newspaper articles that they retweet. What would be the best way to ...
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Word Embedding for Sentiment Analysis
I am working on sentiment analysis of text. I am using keras word embedding.
If my embedding has a vocabulary of 50 and an input length of 4 and I choose an embedding space of 8 dimensions, how will ...
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Deep Learning sentiment analysis model always predicts same class [closed]
I'd really appreciate your help as I'm not an expert in Deep Learning for sentiment analysis and I'm a bit lost.
I'm using the Sentiment140 dataset: http://help.sentiment140.com/for-students
First ...
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How do I normalize or weight document-feature-matrix by length of dictionary entries
What is the best practice way to normalize or weight document-feature-matrices by the length of dictionary entries. Here is some sample code. In reality, my example works with different issues e.g. ...
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Sentiment analysis probabilities
I'm looking into a Kaggle dataset of news article with three columns for the results of sentiment analysis for news items, each about a different company. The columns present the results of ...
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Getting ValueError while implementing LSTM in keras
I am getting this error while implementing LSTM in Keras:
""""Error when checking input: expected lstm_16_input to have 3 dimensions, but got array with shape (156060, 1)""""
I have 156060 text ...
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Can sentiment "analysis" be called sentiment "recognition"? [closed]
In sentiment analysis application of NLP, we are basically required to predict an emotion given a piece of text.
Can we say that we are doing "sentiment recognition" instead of "sentiment analysis" ?...
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Preparing test data for sentiment analysis in Tensor Flow
1) I want to do Sentiment Analysis using RNN + Tensor Flow + (Keras)
2) Is it necessary to prepare test data for sentiment analysis, using RNN, (or any Neural Network), in a certain format ? If so is ...
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Text classification - regularization worsens validation score
I have the text classification problem. Dataset is imbalanced in terms of classes. I'm using StratifiedKFold and balanced weights updating during training LogisticRegression. Let's say my score is:
...
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Delta TF-IDF right choice for multi classification problem
In the paper of Martineau & Finin they describe their new approach with Delta TF-IDF . Instead of measuring how rare features are in the document, they weight these values by how biased they are ...
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How do you use classification algorithms in a sentiment analysis?
Classification algorithms (logistic regression, SVM, etc) work on $(x, y)$ data where $y$ is a categorical (often binary) response and $x$ is a multi-variate predictor.
How are these algorithms ...
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Sklearn logistic regression top coefficients meaning for sentiment analysis
I have a term document matrix, where each element represents the tf-idf value for the given term and document. There are 5000 features (terms) as columns which represents the top 5000 words, and each ...
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Low score in sentiment analysis : how to increase it and maybe deal with class imbalance
It has been 2 weeks now I am working on SemEval task 4 (2016) : Sentiment Analysis on Twitter.
The results I achieve are lower than what I expected for the three class classification problem : ...
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How much data is needed for transfer learning?
I have a pre-trained sentiment classifier on Amazon reviews and I want to use it for transfer learning to classify sentiments on a specific aspect of some products, for example how a person feels ...
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How can you apply sentiment analysis on topic modelling topics?
I need to perform sentiment analysis on topic modelling. I have used LDA with grid search search to identify the topic. The next step would be to perform sentiment analysis on it. How should I go ...
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Sentiment analysis, are my samples significantly different?
I have extracted data from a reviews website. I have created a dictionary with all words that appear in the reviews and corresponding number of counts.
I have then spit the reviews into two samples: ...
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Converting 3-class predictions to single score
I have model predictions for 3 ordinal classes, negative, neutral and positive for the sentiment of a given text. For further analysis I'd like to have only a single number to specify the sentiment of ...
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Train a model Sentiment Analysis scikit learn [closed]
I am getting started with NLP and Sentiment Analysis.
I would like to train a model with Scikit-Learn for detecting the sentiment of tweets.
I have a labeled dataset of tweets, how should I train a ...
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Sentiment Analysis - Emoticon
I am working on an NLP project, my objective is to compute a Sentiment Analysis over short text message.
So far, I did not come up with a solution to account the emoticons. I want to use a machine ...
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