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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29 views

How does Word2Vec actually help with sentimental analysis?

I'm trying read in a whole article, separate the article by sentences, and then words. Then I pass this into the Word2vec Model and the output comes out. However, my goal is to find the positive or ...
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1answer
18 views

Choosing a Change Point Detection Algorithm

I am currently working on a dataset that belongs to the restaurant and food delivery domain. After completing sentiment analysis and quantification, I now need to select a Change Point Detection ...
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1answer
26 views

Label data set for sentiment analysis

I am a beginner in this field. I have a scrapped review data set. It contains review socre (1 - 10) and review content. I am going to label the reviews according to the review score like below : 0-2 -&...
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1answer
28 views

How can the accuracy of the dictionary-based approach be measured and improved?

I recently used TextBlob and the NLTK library to do sentiment analysis. I used both dictionary-based and machine learning-based approaches. It is relatively easy to measure accuracy when we use ...
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1answer
25 views

How to work with hundreds of CSVs with millions of rows in each?

So I'm doing a project on the COVID-19 Tweets dataset from the IEEE port and I plan to analyse the tweets over the time period from March 2020 till date. The thing is there's more than 300 CSVs for ...
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7 views

Google AutoML Sentiment Analysis

I am trying to develop a custom sentiment analysis model on Google AutoML. I have achieved the same, however, I have the following query: Scenario1: I have excluded records from my training data where ...
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23 views

Sentiment Analysis to Predict Stock Movement

I am using news sentiment analysis and machine learning to predict stock market movement. I have two datasets: dataset 1 is historical stock price; dataset 2 is news headlines. After I use VADER to ...
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1answer
24 views

How to predict the sentiment of the entities form the tweet?

I have a JSON file (tweets.json) that contains tweets (sentences) along with the name of the author. Objective 1: Get the most frequent entities from the tweets. Objective 2: Find out the sentiment/...
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30 views

Visualization of SeqSelfAttention layer from Keras

Can someone help me to find, explain and visualize the SeqSelfAttention layer from Keras. I found a lot of flowchart that use the figures from the "attention is all you need paper" where ...
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36 views

Sentiment Analysis Using Neural Networks with Python

I'm working on a task for an assignment for school. The course doesn't have a textbook and instead uses the tutorial on DataCamp. I've struggled severely using DataCamp to learn (been through it ...
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6 views

Class wise opinion for multi-label sentiment classification

I'm trying to build a model which separates positive and negative classes and assigns the label. I have a multi-label review dataset for example: No Review Label 1 Phone is good but charger is not ...
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2answers
24 views

Word list as a baseline for measuring a classifier's performance?

I am working on a simple Naive Bayes classifier that categorizes text messages as either "positive" or "negative". I was told that the simplest baseline to measure the classifier's ...
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14 views

speech emotion recongtion cnn or rnn?

I want to build a speech emotion classifier and I labeled my data into 3 emotions {negative, neutral, positive} the speech files I have are different of length, thus my audio features (mfcc,zcr, etc.) ...
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90 views

How to perform tokenization for tweets in xlnet?

X_train has only one column that contains all tweets. ...
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1answer
18 views

Semantic analysis score as input to LSTM model for improving stock price prediction accuracy [closed]

I have created a univariate LSTM model that is predicting value of Open Price based on last 5 years opening price of a particular stock. I'm getting a decent accuracy. Now, I want to do sentiment ...
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13 views

Why is approximate nearest neighbour with LSH efficient? [closed]

In a brute force nearest neighbour: (consider point in question is 'x', and total number of points is n) calculate distance between x and every other point O(n) Compare all these distances to get the ...
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1answer
47 views

How to implement your own word list for sentiment analysis?

I've finished web scraping and cleaning the text i'm interested in and i also have the sentiment word list i want to apply to it. However, i have a few conceptual and implementation problems. my ...
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27 views

Newspaper analysis

I'm currently working on a project, where I analyze newspaper articles about AI with NLP methods. My research question: Does newspaper coverage focus more on the advantages or disadvantages of AI? I ...
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26 views

create a knowledge base for audio sentiment analysis

do you guys have any idea how to create a knowledge base for audio classification of emotions where i am going to use it for the annotation of the data which i am going to feed it to my deep ...
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22 views

LSTM Train accuracy decreases in training time during the epoch

I'm training an LSTM model for sentiment analysis on a text corpus. There's a thing that I believe is not normal because I never have seen it in training my models. At the start of the epoch, the ...
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1answer
119 views

Validation loss diverging away from the training loss

I used the XLNET for a sentiment classifier in determining whether a comment is positive or negative. I was able to get good results But when I plotted the validation and training losses I saw this ...
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30 views

Subtraction of Positive and Negative Frequencies in Sentiment Analysis

In the Positive Negative Sentiment Analysis, Would it make sense mathematically to instead of keeping a score of the positive frequencies and negative frequencies of a word, calculate the difference ...
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3answers
274 views

Binary classification and numerical labels

I am trying to create a sentiment analysis model using a dataset that have ~50000 positive tweets that i labeled as 1, ~50000 negative tweets that i have labeled as 0. Also i have acquired ~10000 ...
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1answer
14 views

Parse documents to obtain subjective sentiment

I'm working on a project which deals with MRC (Machine Reading Comprehension). I would like a machine to read an article and give me the sentiments based on a provided token. For Instance given the ...
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28 views

“Rare words” on vocabulary

I am trying to create a sentiment analysis model and I have a question. After I preprocessed my tweets and created my vocabulary I've noticed that I have words that appear less than 5 times in my ...
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340 views

ValueError: y should be a 1d array, got an array of shape () instead

I'm using a reviews data and trying to apply classifier model and get prediction. Here is the code i'm trying. ...
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15 views

GloVe word embeddings containing sentiment?

I've been researching sentiment analysis with word embeddings. I read papers that state that word embeddings ignore sentiment information of the words in the text. One paper states that among the top ...
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99 views

NLP Subjectivity Detection methodology?

I am working on a project where I would like to be able to specifically analyze the level of subjectivity in a given text phrase using machine learning. Essentially, I would like to be able to ...
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25 views

k-means for customer review analysis

I have a dataset of amazon Alexa reviews and want to group negative and positive reviews in separate groups. Is k-means a good approach to it? The dataset is unlabeled so how will my model know which ...
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2answers
214 views

Differentiate between positive and negative clusters

I have applied k-means clustering on my dataset of Amazon Alexa reviews. ...
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1answer
28 views

Using BERT for the first time, what are the two columns of my test_results.tsv?

I followed the steps to feed in both dev, test, train.tsv to the model, trained it, then tried to classify test data, and I only have 1 feature, and the classification is binary, 1 or 0. I assumed my ...
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1answer
34 views

making conclusions after sentiment analysis

After performing some sentiment analysis, I have a dataset that looks like this: For different products, using online reviews, I have obtained some values for positive/negative sentiments. However, ...
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0answers
24 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 ...
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55 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... ...
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1answer
30 views

Bug in sentiment analysis and classification for unlabeled text [closed]

I'm working on the transcript of Trump and Biden's debate and want to analyze the sentences and classify negative, positive, or neutral comments, but I ran into one problem. I used both TextBlob and ...
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2answers
517 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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1answer
42 views

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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2answers
47 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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1answer
152 views

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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2answers
36 views

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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1answer
29 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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24 views

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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2answers
44 views

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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2answers
165 views

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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0answers
227 views

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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1answer
543 views

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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1answer
57 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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2answers
36 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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15 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 ...
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1answer
82 views

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 ...