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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33 views

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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Sentiment Analysis on Software Engineering texts

What are the possible ways to improve sentiment dictionaries to analyse SE texts? There are several SE specific sentiment dictionaries but cannot expect much accuracy when analysing open-source ...
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11 views

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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42 views

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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15 views

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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21 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 ...
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17 views

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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18 views

Which steps are involved in sentiment analysis with Huggingface Transformers?

I want to perform a sentiment analysis of a dataset of (Spanish) tweets about COVID-19 vaccines. I've already scraped the tweets and identified a pretrained model I can use for Spanish. What I don't ...
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18 views

What do we mean as Positive or Negative in Sentiment Analysis?

What do we mean in Sentiment Analysis NLP when it is said a sentence is positive or negative? I think I need to specify this regarding any other parameter. For example "iPhone is good" is a ...
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14 views

calculating score for the sentiment

I am working on the sentiment project. I have used the BERT model. Now I need to generate a score for the sentiment of each sentence. I don't have any idea what would be the potential approach to do ...
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Is it possible to train a model for sentiment analysis with data that has been labeled with VADER?

I want to perform sentiment analysis on a selection of tweets regarding vaccination. The tweets I find are either unlabeled or have been labeled using VADER or TextBlob. I am wondering if it makes ...
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Who is supposed to label my sentiment analysis? Linguistics or psychologist?

I'm starting off my undergraduate research on text classification even though I'm still considered new to this topic. I've collected more than 20K data from Twitter. I've been trying to label the data ...
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1answer
26 views

Can I use a pre-trained model for sentiment analysis/text classification of unlabelled data?

I'm planning on working on a project where I'll have a large collection of tweets about coronavirus vaccines. None of the tweets will have a label (e.g. positive, neutral, negative). Therefore I won't ...
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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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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
32 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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37 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
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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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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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26 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
44 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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38 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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41 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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7 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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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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163 views

How to perform tokenization for tweets in xlnet?

X_train has only one column that contains all tweets. ...
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22 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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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
73 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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25 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
177 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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34 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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330 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
16 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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1answer
29 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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606 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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129 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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26 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
253 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
37 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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39 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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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... ...