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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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averaging multiple scores on small chunks of data or raw score on single collated data

I am using IBM Watson tool to determine tones (https://tone-analyzer-demo.mybluemix.net/) and personality scores (https://personality-insights-livedemo.mybluemix.net/) on different files containing ...
div's user avatar
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3 votes
1 answer
409 views

Weighting of words in lexicon based sentiment analysis

I have a a question regarding my current project, i am trying to do a lexicon based sentiment analysis on my data, where i calculate the sentiment score as following: $$ Score = \frac{\sum_{i}{word_i}...
voltage's user avatar
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3 votes
1 answer
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measuring flip-flop behaviour across several topics

I'm trying to analyze a behavior called "sentiment flipping" of users in a dataset, but I'm not able to step on. Let's suppose that I have two groups of users, say them good and bad users. My ...
Minions's user avatar
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2 votes
3 answers
213 views

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 ...
mikeman's user avatar
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2 votes
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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 ...
Dan K's user avatar
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2 votes
0 answers
342 views

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 ...
maldini425's user avatar
2 votes
1 answer
161 views

Binary + Neutral Classification

I have a dataset of posts for sentiment analysis that are labelled with -1 (negative), 1 (positive) or 0 (neutral). So I wonder how should I deal with that. These are my ideas: make a multiclass ...
EzrielS's user avatar
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2 votes
1 answer
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Question about balancing training data for sentiment analysis (machine learning)

My question is about when to balance training data for sentiment analysis. Upon evaluating my training dataset, which has 3 labels (good, bad, neutral), I noticed there were twice as many neutral ...
Nore's user avatar
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2 votes
0 answers
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List of CNN for Emotion/Sentiment recognition on images with performance on main datasets (IAPS, GAPED, EmoPics, NAPS)

There are more and more databases of pictures classified or rated with emotions. For instance, I know of 4 databases (IAPS, GAPED, EmoPics, NAPS) rating pictures on 2 dimensions: Valance (positive vs ...
RemiDav's user avatar
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2 votes
1 answer
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How to classify neutral sentiments using BERT

We can do text classification as positive and negative as mentioned in below notebook. But is there any way to classify neutral sentiment also? https://colab.research.google.com/github/google-...
Prashanth's user avatar
2 votes
0 answers
33 views

How do I perform Sentiment Analysis on Tweets in the following pattern:

I have tweets obtained based on matches (football) before the match begins. I have tweets which specify a team will win 3-1 and so on which are easily analyzed using regular expressions. I am facing ...
Wila Wuz's user avatar
1 vote
1 answer
786 views

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 ...
Alberto De Benedittis's user avatar
1 vote
1 answer
148 views

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 ...
ViennaMike's user avatar
1 vote
0 answers
14 views

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 ...
Soroush Mirzaei's user avatar
1 vote
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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 ...
Soroush Mirzaei's user avatar
1 vote
0 answers
41 views

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 : <...
Abdulmoty's user avatar
1 vote
1 answer
394 views

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 ...
geekPinkFlower's user avatar
1 vote
0 answers
371 views

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 ...
vgoklani's user avatar
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1 vote
0 answers
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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 ...
def __init__'s user avatar
1 vote
0 answers
366 views

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 ...
LeLuc's user avatar
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1 vote
1 answer
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I am getting this error ValueError: not enough values to unpack (expected 4, got 2)

I have written this code: ...
Yhogi Alawdi's user avatar
1 vote
0 answers
56 views

How to find parts of text that answer a "why"

Given some text that describes something, how to tag / identify parts of the text that explain specific aspects - what, who, why? For example, given the following input text... ...
TheCodeArtist's user avatar
1 vote
0 answers
18 views

Embedding layers trained on Amazon Reviews

I am working on research to perform sentiment analysis on Amazon reviews. My data is not labelled so I am now using Lexicon based sentiment analysis such as Vader. I am wondering if it is possible to ...
user3425989's user avatar
1 vote
0 answers
19 views

What is the input dimension for this keras model?

I'm doing a tutorial, where I have to evaluate the sentiment of IMDB reviews, positive or negative. I first created an index for each word and then replaced every word in each review for each ...
Pedro's user avatar
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1 vote
0 answers
17 views

Normalizing impact of outnumbered positive reviews to extract sentiment of each term

I'm trying to extract the sentiment of Italian words using reviews that users wrote on Italian amazon. After doing some cleaning (remove punctuation, stop-words, etc.) I used this method to get the ...
Mehdi Abbassi's user avatar
1 vote
0 answers
84 views

Sentiment Analysis: using a dataset (IMDB reviews) to train a neural-net and using it to predict entirely different datasets (Political articles)

We need to analyse a lot of articles relevant to political instability in a given country (things like the possibility of a coalition / a snap election etc). The problem is that I could not find any ...
Nishant Parmar's user avatar
1 vote
0 answers
99 views

Sentiment Analysis for Q&A based reviews

I'm a self-learning ML enthusiast and I recently started learning NLP and performing Sentiment Analysis on imdb, yelp, amazon datasets(using Python). I came across a dataset where the reviews were in ...
lucifer's user avatar
  • 11
1 vote
1 answer
634 views

Sentiment Analysis of News Headlines

I'm trying to do sentiment analysis of News Headlines about a particular subject mentioned in it. Initially, I used TextBlob library for sentiment analysis to ...
Mayank Lal's user avatar
1 vote
1 answer
73 views

Emotional tension score in sentences

I am beginner in natural language processing and my goal is to find a way to score sentences based on their emotional tension. More specifically, I would like to know to what degree a sentence ...
amiref's user avatar
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1 vote
0 answers
28 views

Customer Demographic Data

I am looking for two types of data Demographic data Is there a vendor or data source that could provide demographic information of customers who buy a product? It doesn't include personal ...
user2979630's user avatar
1 vote
1 answer
73 views

Optimize F-Score only for certain classes, disregard other classes

I have a labeled dataset of product reviews where the label is a rating between 1 and 5 and the review is just text. I use a simple naive Bayes classifier (sklearn) to try to predict a rating given a ...
Patric's user avatar
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1 vote
1 answer
198 views

Deciding Initial Weights In A Linear Classifier For Sentiment Analysis

I would like to build a simple sentiment analysis classifier using logistic regression. I downloaded a list of positive and negative words from cs.uic.edu. There are more than 6000 words both positive ...
Suhail Gupta's user avatar
1 vote
0 answers
69 views

Feedback Analysis

We are trying to rank the products on the basis of score, score is calculated by analyzing the good or bad feedback about the product. After a lot of research and analysis we came up with this formula ...
Faizan khan's user avatar
1 vote
0 answers
174 views

Sentiment analysis with continuous scale for responses

I am trying to create a sentiment analysis system using deep learning (with R). I have a review base of customer reviews which for each review the customer make a mark (from 0 to 10). How can I do ...
Poisson's user avatar
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0 answers
5 views

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....
Sorta Gud's user avatar
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0 answers
43 views

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 ...
Devansh Gupta's user avatar
0 votes
0 answers
27 views

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 ...
Devansh Gupta's user avatar
0 votes
1 answer
65 views

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 ...
Devansh Gupta's user avatar
0 votes
0 answers
22 views

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 ...
m sh's user avatar
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0 votes
0 answers
18 views

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 ...
mehmet's user avatar
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0 votes
1 answer
65 views

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 ...
Medhat's user avatar
  • 1
0 votes
1 answer
98 views

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....
m sh's user avatar
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0 votes
0 answers
26 views

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.
Hani's user avatar
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0 votes
0 answers
25 views

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: ...
pedritoanonimo's user avatar
0 votes
1 answer
92 views

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 ...
m sh's user avatar
  • 3
0 votes
0 answers
31 views

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 ...
Ryan Watts's user avatar
0 votes
2 answers
242 views

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 ...
Dan Jírovec's user avatar
0 votes
1 answer
274 views

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 ...
Rajdeep Biswas's user avatar
0 votes
0 answers
44 views

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 ...
nem0's user avatar
  • 9
0 votes
0 answers
43 views

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:/...
Bluetail's user avatar
  • 111