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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Reinforcement learning
I am working on a sentiment analysis project. I used BERT model for training but lack of data it gives huge overfitting. So after i moved LLM approach to do that. Using LLM finally i got good results....
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Why is Spacy sentiment score 0.0 for a sentence?
I'm trying to get a sentence's sentiment score using Spacy and apparently every sentence I pass gets a score of 0.0. Can someone help me understand what's going wrong here?
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How to created a sentiment analysis metric from individual pieces of data
I have an array of news articles I get daily. I run a sentiment model and get a value between -1.5 and 1.5. My question is how do I combine each say days worth of individual values between -1.5 and 1....
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Simple sentiment analysis model gives stupid accuracy
I am working on a sentiment analysis model from scratch but I ran into issues so thought I'd implement one using pytorch and then replicate but I also ran into issues with the pytorch version.
I'm not ...
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Confusion with FC Layer Neurons and Output Shapes in CNN-based Sentiment Analysis Model
I am currently working on a sentiment analysis model for text data, and I'm using a Convolutional Neural Network (CNN) architecture. This is my first time implementing a CNN, and I'm facing issues ...
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Issue with Convolutional Layer in Python: Getting All Zeros in Output and Terminating at a Certain Iteration
I'm currently working on implementing a convolutional layer in Python for a natural language processing model. However, I've encountered an issue with the convolutional layer that I can't seem to ...
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Sentiment extraction with hugging face ready to use model
I have a set of reviews for which I need to extract their sentiments and use those sentiments as an independent variable in an econometric model. I used one of the ready-to-use models of hugging face ...
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multi label multi class classification problem
I am trying to solve a aspect based sentiment analysis problem.
I am considering to devise a NN but am not sure if it is doable the way I am doing.
here is how I structure it.
I have a training set of ...
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Sentiment Analysis on the first 100 words of a very large essay of 500/700 words
Are there any potential issues on performing sentiment analysis using the first 100 words of a very large essay that is of 500 to 700 words. I am having to do this because since most transformer ...
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Why my sentiment analysis model is overfitting?
The task is to predict sentiment from 1 to 10 based on Russian reviews. The training data size is 20000 records, of which 1000 were preserved as a validation set. The preprocessing steps included ...
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Bert model for document sentiment classification
I am trying to fine-tune a Bert model for sentiment analysis. Instead of one sentence, my inputs are documents (including several sentences) and I am not removing dots. I was wondering if is it okay ...
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Dealing with rich vocabulary and a low average frequency of words in NLP
What is the best way to deal with a dataset that has a rich vocabulary and a low average frequency of words that is showing low validation accuracy?
While reading online I saw many people recommending ...
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SemEval-2016 Task 5 Subtask 2 Evaluation
Hi, I read SEMEVAL task 5 from this website (https://alt.qcri.org/semeval2016/task5/) but the evaluation method for subtask 2 is not clear. I really appreciate it if you tell me the method. This is ...
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Aspect-Based Sentiment Analysis with Bert and Pytorch
I have a dataset of online reviews (X) with their corresponding topics (topic1 to topic5) and each topic can have 5 values (fined-grained sentiment score from 1 to 5). So, I have one X and 5 Y columns....
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LDA calculations manually
my question: has anyone ever done LDA calculations manually? I have difficulty in manual calculation. can someone help me to teach me for lda calculations manually.
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Multilingual Sentiment Analysis in orange
I have an issue with multilingual sentiment analysis using orange data mining. Everytime I tried using the widget, It gave me 0 score sentiment for all tweets data. I didn't know the problem.
FYI, my ...
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unbalanced data on train set and test set
I already have 2 datasets. One to use for training and one for testing.
Both datasets are unbalanced (with similar percentages), with around 90% of label 1 .
Will it be useful to balance the data if ...
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How does BERT work for Aspect-Based sentiment analysis?
I have recently used a package to perform Aspect-Based Sentiment Analysis (ABSA) through a BERT model.
Briefly, the model takes two inputs:
words that constitute the aspects
a sentence on which we ...
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Sentiment analysis BERT vs Model from scratch
I am working on building a sentiment analyzer, the data I would like to analyze is social media data from twitter, once I have created a the model I want to integrate it into a simply webpage.
I have ...
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Sentiment Analysis scoring and negatives
I have already calculated the Polarity of my comments in my df and now I'm trying to create a column that says "negative", "positive" or "Neutral" based off the polarity ...
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What models/techniques can I use to generalize industry specific datasets?
I have a few dictionaries pertaining to different industries (ie. tech, manufacturing, education, etc.). These dictionaries map phrases and keywords to a sentiment score. I'd like to create a ...
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How to combine topic modelling and aspect based sentiment analysis?
I have a large set of reviews on which I performed topic modelling.
Now that I have extracted topics, I would like to use them to perform Aspect Based Sentiment Analysis.
I was trying to use this ...
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Alternatives to twitter for large daily or weekly samples for sentiment analysis
Twitter, with their API, including the free tier, has been a go-to source for collecting large samples of texts expressing sentiment on various topics of interest. I just started a project in December ...
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FinBERT out of the box performance testing
I'm trying to perform an out of the box performance test for FinBERT using the financialphrasebank dataset(sentiment analysis) to get a baseline performance before I start finetuning the model. The ...
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model interaction between words for a sentiment analysis task
I am wondering what is the most appropriate way to model the interaction between two words/variables in a language model for a sentiment analysis task. For example, in the following dataset:
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Compound and Complex Sentence Tokenization
I am trying to tokenize sentences of a document for aspect-based sentiment analysis. There are some sentences that consist of more than one topic. For example, " The touch screen is good but the ...
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Text Annotation
How to annotate aspect-based sentiment analysis using docanno? I want to annotate data like the given piture
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Abstracted text summarisation and generation from weighted keywords
Suppose I have a list of weighted keywords/phrases, such as "solar panel", "rooftop", etc. The weights are in [0,1] with higher weights indicating a stronger preference for ...
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Is there any sentiment analysis algorithm to identify sentiment of a sentence towards a certain word in the sentence?
I'll start with some examples. Think about a sentence like "Mazda CX5 is a good car.". NLTK sentiment analysis module "Vader" will give a positive polarity score on the sentence. ...
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Procedure or term for analyzing transcribed text and returning bulleted output
I am attempting to analyze transcribed text from an audio file to group bullet points based on known key phrases in the text.
Example: I have verbally stated the following keywords in the text, which ...
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How to get all 3 labels' sentiment from finbert instead of the most likely label's?
I'm using bert to do sentiment analysis. I previous used cardiffnlp's twitter-roberta-base-sentiment, https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment.
It gives the the usage on its ...
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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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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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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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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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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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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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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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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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