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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16 views

How is it possible for RNN to do sentiment analysis?

I'm wondering how RNN can be used when doing sentiment analysis. It seems that the characteristic of RNN is to remember what appeared in the past and determine the value of the present (future), but I ...
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Text mining in Amazon product review using R. I wasn't able to extract the particular product's review

Text mining on Amazon product review using R Program. I wasn't able to extract the particular product's review(i.e.If iphone 11 has 6k review, I need to extract all of it.) I'm getting only one column ...
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37 views

Summing three lexicon based approach methods for sentiment analysis?

I'm doing sentiment analysis using a lexicon based approach and I have a bunch of news headlines that needs to be categorized as negative, positive and neutral or within a scale ranging from -1 (very ...
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Bechmark models for Text Classification / Sentiment Classification

I am currently working on a novel application in NLP where I try to classify empathic and non-empathic texts. I would like to compare the performance of my model to some benchmark models. As I am ...
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Is it possible to predict sentiment of unlabelled dataset using BERT?

I have a large unlabeled dataset and I want to predict sentiment for each document in this dataset. I want to know, is it possible that I can use BERT for sentiment analysis of unlabeled data? I have ...
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Sentiment Analysis on long and structured texts

I'm trying to learn how sentiment analysis based on machine learning techniques works by reading guides online and papers from the academia world and I'm struggling to understand the following: Why ...
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19 views

Which tool is good to collect tweets on 50 keywords over the last 5 years and then analyze them with the LDA algorithm or sentiment analysis?

I want to find tweets from the last 5 years to a topic. For this I decide for 50 Keywords (related to the main topic), where I want to find data on Twitter. I want to find out how the trend on the ...
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How are the Google Cloud Natural Language API Sentiment Analysis outputs interpreted?

I am trying to get a better understanding of the outputs given by Google's sentiment analysis API. It takes in a sentence and gives out two values - magnitude and <...
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Sentiment analysis of the target in articles

The goal is as follows: I have a big article and I want to define the sentiment of the particular word. For example, the article describes pros and cons of bikes and cars and I want to find the ...
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21 views

how can i create a sentiment analysis model and use it on dataframe

I am new to AI and sentiment analysis and i tried to write a python script that allow user to import a csv file that includes tweets(as Dataset ) and apply the script on this dataset in order to ...
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Reduce the risk of numerical underflow

We use log-likelihood (called as lambda) to reduce the risk of numerical underflow (in context of sentiment analysis using Naive Bayes). What does "reduce the risk of numerical underflow" ...
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Does GPT-2 has pre trained for sentiment analysis?

I tried sentiment analysis with 345M model of GPT-2. But it took a long time to train. So is there any other GPT-2 model available for sentiment analysis?
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How to make use of POS tags as useful features for a NaiveBayesClassifier for sentiment analysis?

I'm doing sentiment analysis on a twitter dataset (problem link). I have extracted the POS tags from the tweets and created tfidf vectors from the POS tags and used them as a feature (got accuracy of ...
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21 views

Unsupervised Sentimental Analysis in R

How would you evaluate unsupervised sentimental analysis? I am reading on evaluating sentimental analysis and learning that much of the classification models that are being used, the data has target/...
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31 views

Build a sentiment model from scratch

I would like to know how I can create a sentiment model from scratch. I have my data, list of texts, with no labels about sentiment. ...
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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 ...
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Sentiment analysis of tweets (Train model on a labelled dataset and use on some other unlabelled data)

I have a huge amount of tweets on a particular topic say 'ABC' and the data is not labelled. I want to perform multi-class sentiment analysis of these tweets. I tried many unsupervised clustering ...
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Vader vs TextBlob opposite outcome: why?

I've been studying for a Data Science course and yesterday I was challenged with a sentiment analysis, for which tons of material can be found online. So bear with me, ad I'm trying to get to the ...
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Biasing SVM algorithm towards particular subset of data

I'm training an SVM model for sentiment analysis, based on social media data eg. tweets. The model will be trained using a small selection of a particular company's tweets in order to classify new ...
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Loaded model predicts well in colab but gives same label and accuracy when downloaded

I have developed a Recurrent Neural Network to perform sentiment analysis on tweets using the Kazanova/sentiment140 dataset in Kaggle. The model looks like this: ...
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Constituency vs Dependency Parsing: What is more effective for Sentiment Analysis?

Parsing is often used to understand the sentiment of complex sentences filled with double negations or very articulated. There are two main ways of parsing a sentence: Constituency and Dependency ...
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Using BM25 to rank words

How effective is it to use BM25 to rank words, to be more specific i have a dictionary of words and i want to rank only words in a document that are also in my dictionary. I want to rank all words in ...
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1answer
25 views

How to add a new column with labels in a dataframe?

I have thousands of sentences that I would need to label based on their sentiment. An example is ...
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281 views

BPE vs WordPiece Tokenization - when to use / which?

What's the general tradeoff between choosing BPE vs WordPiece Tokenization? When is one preferable to the other? Are there any differences in model performance between the two? I'm looking for a ...
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Text analysis: structure and sentiment

I would need to analyse the structure of texts like this: ...
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31 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}...
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How to build a dictionary for sentiment analysis?

I would like to know if it would be possible to build a dictionary using terms/words included in a dataset, in order to be used for sentiment analysis (and build a sentiment analysis classification ...
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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 ...
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33 views

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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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 ...
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How Yelp System Detects Paid Reviews

I am wondering how the yelp spam detection system detects paid reviews? By paid, I mean the following scenarios: I as a business owner pay people to write positive comments and give me a good rate I ...
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91 views

Degree of Profanity in a Sentence [closed]

Given a comment or a sentence and a list of profane words, How do I write a program to print the degree of profanity in that sentence?
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Explanation for Why Logistic Regression can be so Accurate in Sentiment Classification?

My question is about how a logistic regression model performs so accurately. In some exploratory experimentation, I compared a logistic regression model against a long short term memory recurrent ...
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42 views

Sentiment Analysis Label Distribution

I am working on Sentiment Analysis model. The dataset I have has three labels POSITIVE , NEGATIVE and NEUTRAL But the problem is the data is not equal for labels. Say out of 100K , 75 K are neutral, ...
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Normalizing impact of outnumbered positive reviews to extract sentiment of each term

I'm trying to extract sentiment of Italian words using reviews that users wrote in Italian amazon. After doing some cleaning (remove punctuation, stop-words, etc.) I used this method to get the ...
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532 views

Using Trainable=True in Keras Embedding obtained better performance

It is suggested by the author of Keras [1] to use Trainable=False when using the embedding layer in Keras to prevent the weights from being updated during training. ...
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593 views

Decision tree in sentiment analysis

Creating a classifier to do "Sentiment Analysis" can be done with several algorithms like SVM, KNN, Neural networks,Decision tree... and lately i have read about Decision tree and how it works and i ...
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1answer
139 views

Using TF-IDF for feature extraction in Sentiment Analysis

I am working on sentiment analysis for twitter data, for which I have used Vader to get an approximation of sentiment for a tweet. Along with, I have used TF-IDF for feature extraction. These feature ...
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3k views

What is purpose of the [CLS] token and why its encoding output is important?

I am reading this article on how to use BERT by Jay Alammar and I understand things up until: For sentence classification, we’re only only interested in BERT’s output for the [CLS] token, so we ...
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24 views

Doubt on retrieving tweets for sentiment analysis?

I wanted to do my first project on sentiment analysis. My goal is trying to do sentiment analysis on tweets that mention 'Uber' and see if there is correlation with the stock price: 'UBER'. Problem ...
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2answers
294 views

Difference between packaged sentiment analysis tools (TextBlob/NLTK) and training your own classifier?

I'm new to ML and training classifiers in practice, so I was just wondering what the difference was between the built-in sentiment tools of packages such as NLTK and TextBlob as compared to manually ...
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1answer
136 views

What is Sentiment Bias? How will it affect a Lexicon Based Sentiment Analysis?

I am comparing deep learning and lexicon/rule-based models for sentiment analysis. When I was doing some research into the limitations of lexicon based models, I came across a journal article that ...
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37 views

How to extract sub sentences from sentence mentioning a particular subject?

I am trying to solve an NLP problem. For a given sentence like : "The Pasta was delicious, the Pizza was average" I want to extract the sentiment attached to food items. Having built my own NER ...
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2answers
46 views

What does Conv1d do in a sentiment analysis?

I am doing some study on https://www.kaggle.com/anshulrai/cudnnlstm-implementation-93-7-accuracy I understand we need LSTM to capture the sequence of words in the sentience, but I am not quite ...
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1answer
26 views

Analyzing Sentiments of Financial News related to a Company

I'm trying to build a model which gives me the sentiments of the Financial News related to a company and I want to predict the stock price accordingly. But the major problem that I'm facing is ...
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161 views

Using LSTM for binary text Classification, getting almost same accuracy at each epoch

I am doing Twitter sentiment classification. For that I am using LSTM with pretrained 50d GloVe word embeddings(not training them as of now, might do in future). The tweets are of variable lengths ...
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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 ...
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2answers
167 views

How to justify the usage of 200 dimensions in word vectors instead of the 300 dimensions?

When employing machine learning methods in NLP, most of studies use 200 or 300 dimensional vectors. 300 dimensional embeddings carry more information and this, therefore, is considered to produce ...
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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 ...
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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 ...