Questions tagged [sentiment-analysis]

Sentiment analysis refers to categorizing some given data as to what sentiment(s) it expresses. Usually, it refers to extracting sentiment from a text, e.g. tweets or blog posts.

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Is It Fundamentally Correct To The Text Classification Model To Train First Without Pre-Trained Word Vectors And Then With Pre-Trained Word Vectors?

Is this solution fundamentally correct to the text classification (sentiment analysis) model to train it by these three steps: train the model without pre-trained word vectors untill reaches the ...
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Is This Solution Fundamentally Correct To The Text Classification Model With Pre-Trained Word Vectors?

Is it fundamentally correct to training text classification (sentiment analysis) model with pre-trained word vectors; first with the locked embedding layer, and then train again with locked additional ...
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Sentiment Analysis on Twitter data

I would like to do sentiment analysis on Tweets. The algorithm should serve as a background check if we want to hire someone, but it can also give us a general feeling for customers. Say you launch a ...
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What is the pooled output when using tensorflows implementation of BERT for text classification (multiple sentences)

I stumbled upon different sources that state that each sentence starts with a CLS token when passed to BERT. I'm passing text documents with multiple sentences to BERT. This would mean that for each ...
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Using a fine-tuned model for a different dataset

I have a dataset of different sentences from news articles which I need to classify by their sentiment. For that goal I'm planning to use a fine-tuned model which was fine-tuned on different datasets, ...
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Is there anyway to classify the category on give amazon reviews using python

I am trying to find a model or way to classify text which falls into a category and its a positive or negative feedback. For ex. we have three columns Review : Camera's not good battery backup is not ...
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Labeling a dataset for sentiment analysis

I was reading articles on sentiment analysis and NLP and there is something I cant quite understand. One of the methods to label a dataset is to use something like textblob with a polarity dictionary ...
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How to deal with one output for multiple inputs?

Hei! I want to train a model, that predicts the sentiment of news headlines. I've got multiple unordered news headlines per day, but one sentiment score. What is a convenient solution to overcome the ...
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Training data in sentiment analysis

I'm doing sentiment analysis of tweets related to recent acquisition of Twitter by Elon Musk. I have a corpus of 10 000 tweets and I'd like to use machine learning methods using models like SVM and ...
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getting actual concepts value instead of its URI in ontology

I am using owl ontology for semantic analysis in emotional sentiment analysis project , I am trying to navigate the ontology to check a concepts and its relation , my ontology has classes like this : <...
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Why (or how) does a Keras model skip Stemming or Lemmatization steps?

This Keras article / tutorial here does perform text standardization i.e removing HTML elements, punctuation, etc. from the text dataset, however, there is a distinct lack of any stemming or ...
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Are the word of women and men different when expressing their views on the same subject?

My data includes women's comments on X and Y and men's comments on X and Y. Each comment is of equal length. I will calculate how much different the word choice between men and women when commenting ...
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predictive effect in the classification made according to the comments in different fields

I want to do a classification through comments categorized in 4 areas(X,Y,Z,M). Categorizing the product as good or bad based on the comments in the fields X, Y, Z, M. How can I follow a path to see ...
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Using VADER Sentiment Analysis makes distributions overlap : how to improve my model

I use VADER Sentiment Analysis on a "customer reviews" dataset. VADER breaks down feelings of satisfaction and dissatisfaction into neutral and positive negative components. Plotting the ...
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MXNet for nltk.sentiment.vader?

Is the nltk.sentiment.vader sentiment analyzer available in MXNet format? If so where can it be downloaded?
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How to increase the model accuracy and how to choose the number of epochs in a LSTM model from accuracy and loss curves?

I am doing a NLP sentiment analysis task using an LSTM model (which currently gives me a 50% test accuracy as compared to 84% of a Naive Bayes). It is a text corpus of movie reviews from here (https:/...
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Labelling a dataset for sentiment analysis, which model is the best?

I want to do some sentiment analysis on a large text dataset I scraped. From what I've learned so far, I know that I need to either manually label each text data (positive, negative, neutral) or use a ...
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Training a model with a series of text responses as input

I want to train a binary classifier on text -- so something like sentiment analysis, but my input vectors are going to be a series of responses from some user separated by some separator character. I ...
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When I'm trying Logistics Regression, am getting this error "ValueError: Found input variables with inconsistent numbers of samples: [1, 12500]"

Here is my code: ...
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I don't know why this AttributeError: 'numpy.ndarray' object has no attribute 'lower' occurs

I'm trying to run a linear regression. But I'm getting this "AttributeError: 'numpy.ndarray' object has no attribute 'lower' " Here's the code I'using: ...
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AraBERT Overfitting for sentiment analysis

I Am newbie to Machine Learning in general. I am currently trying to follow a tutorial on sentiment analysis using BERT and Transformers. I do not know how i can Read the results to know the ...
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LSTM for sentiment analysis

I saw this tensorflow model which is used for telling if text is positive or negative, and I don't fully understand it. I know that LSTM saves the words and predict the next words based on the ...
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Can Domain-Adaption improve the performance of Sentiment Analysis?

Does Domain Adaption have any effect of results in Sentiment Analysis? I am going to train a BERT language model based on some texts particularly in Health area, then I want to apply Opinion Mining on ...
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Should we clean text data before applying Vader for getting sentiment

What I meant by data cleaning is that Removing Punctuations Lower Casing Removing Stop words Removing irrelevant symbols, links and emojis According to my knowledge, things like Punctuations, ...
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Transformer model comparison for binary sentiment classification

On two independent datasets, I am comparing XLNet and BERT models with binary sentiment classification tasks: the Twitter dataset, where sentences are short, and the IMDB review dataset, where ...
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How to fit Word2Vec on test data?

I am working on a Sentiment Analysis problem. I am using Gensim's Word2Vec to vectorize my data in the following way: ...
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Dimension error when tuning LSTM layer

I am working on a sentiment analysis problem which is a binary classification. These are some of the parameters that might be useful: 1.) Length of train list = 203 2.) Length of test list = 51 3.) ...
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How to get fine-grained sentiment score from text data under unsupervised learning?

In my experience I have only used LSTM models to do sentiment classification tasks on text data under supervised learning. For example, the imdb dataset from keras which is a binary classification ...
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Splitting sentiment analysis training data into x-train and y-train for a RNN?

Suppose I have a dataset of comments from users, around multiple websites, such that in each row, there are two comments, and one is considered more 'negative' and one more 'positive' indicated by the ...
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NLP with what to replace names in sentences?

My task is named entity-sentiment analysis, and I see if I change the name in the sentence then sentiment can change. Are there any methods to avoid this problem? I think to replace these words with ...
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Get the keywords from positive and negative reviews

I have trained a classifier algorithm on a sentiment analysis model which classifies the reviews scraped off Amazon as Positive or Negative. Now for each class, I want to get the keywords from the ...
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Clustering text data based on sentiment?

I am scraping reviews off Amazon with the intent to perform sentiment analysis to classify them into positve, negative and neutral. Now the data I would get would be text and unlabeled. My approach to ...
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Twitter Sentiment Analysis: problem in predicting [closed]

I am going to do Sentiment Analysis over some tweets. The goal is to find out which post is with and which one is against a specific topic(which tweet is saying this product is good and which on is ...
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How to properly perform sentiment analysis?

How to properly perform sentiment analysis for text with 300-600 words? If I use TextBlob and clean my data and remove stopwords(extended words and comma backslash..etc) do I need to tokenize the ...
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What is the difference between rule based & feature based methods in sentiment analysis?

if I use TextBlob in Python to get data label 0/1 of texts (postive/negative) and then use logistic regression for training and prediction, is this feature method or rule based method?
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Softmax in Sentiment analysis

I am going to do Sentiment Analysis over some tweet texts. So, in summary we have three classes: Positive, Neutral, Negative. If I apply Softmax in the last layer, I will have the probability for each ...
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Classification issues with Binary Sentiment analysis

I am trying to conduct a binary sentiment analysis of Arabic text (i.e. either classifying social media posts into negative/positive). I built a basic dictionary that covers all words included in the ...
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Creating a Sentiment dictionary from scratch

I am analyzing Arabic textual data from a social media forum discussing economic issues such as labor unions. I am using a package that classifies as negative, positive, or neutral. For instance, the ...
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3 votes
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I can't figure out how to improve accuracy for tweet sentiment

I'm doing a beginning attempt at tweet sentiment analysis (positive, neutral, negative). So far I have cleaned the data and used a BoW to get some feeling of the data (>2.5k tweets). I also made ...
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How to Fine Tune a BERT model for sentiment analysis to get the best f1 score

I am building a multi-class sentiment analysis BERT model that's optimized to give the best f1 score. More specifically, I train each epoch by optimizing binary cross entropy per class, taking the ...
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Overlap between the training and testing set in cross validation settings

Why is it important to evaluate models using a cross-validation setting where the training and test sets have no overlap? I noticed that a violation of this guideline exaggerates the effectiveness of ...
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How to consider the effect of exclamation marks in sentiment analysis

For example in the following two tweets, we can see the first one seems to be more negative than the second one: "You are not required to come here now!!!" "You are not required to ...
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What effect repetitive data will have on the performance of the model

I understand that my question is very broad and that the correct answer may depend on various things. I want to get an idea in general what we may expect if we have repetitive data in our dataset. ...
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When to do tokenization and does my output need tokenization after stemming?

I am working on sentiment analysis project , where there are various customer reviews. So I am trying to clean those reviews. So first thing i did is removing special characters, white spaces, ...
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How to improve the result of f1 on imbalanced dataset

I have a dataset in which these are the distribution of the data: Neutral. 15000 Negative 3000 positive 2000 And I am mostly interested to improve the ...
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How to evaluate an aspect based sentiment analysis model?

I have a model X that takes a review and predict the position of the aspect and the polarity: ...
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Word count with map reduce

Suppose we use an input file that contains the following lyrics from a famous song: We’re up all night till the sun We’re up all night to get some The input pairs for the Map phase will be the ...
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Video Sentiment Analysis

I am trying to build a video sentiment analysis feature in python which will take a video and provide the sentiments different people are expressing based on facial expressions in the video. Is there ...
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Is it possible to fine-tune a (Spanish RoBERTa) model for a different task?

I'm doing sentiment analysis of Spanish tweets. After reviewing some of the recent literature, I've seen that there's been a most recent effort to train a RoBERTa model exclusively on Spanish text. It ...
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How to get sentiment score for a word in a given dataset

I have a sentiment analysis dataset that is labeled in three categories: positive, negative, and neutral. I also have a list of words (mostly nouns), for which I want to calculate the sentiment value, ...
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