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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using dataset to classifying and labelling another unlabeded dataset

I collect a collection of posts from Facebook and I use a published sentiment datset to labeling my collected dataset. is this a right technique and what its name is this transfer-learning ?
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Combining heterogeneous data sets for more powerful machine learning

Suppose we have two data sets of movie reviews; one from IMDB and one from Rotten Tomatoes (RT). Each entry has a written-review and a score attached to it. The concatenated datasets might look like ...
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Testing accuracy has very high accuracy metrics on epoch 1 but decreases rapidly on following epochs

For a binary classification problem my testing accuracy metrics are very high on epoch 1 but it decreases rapidly on further epochs, training trends are similar with epoch 1 having low accuracy ...
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33 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 ...
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Twitter Dataset

I have found the following dataset, apparently it is the largest tweet dataset: https://www.kaggle.com/kazanova/sentiment140 However, I am looking for a dataset of tweets, with columns containing: ...
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Using doccano for Aspect Based Sentiment Analysis annotation

Currently looking for a good tool to annotate sentences regarding aspects and their respective sentiment polarities. I'm using SemEval Task 4 as a reference. The following is an example in the ...
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33 views

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-...
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30 views

What's the fastest way to do a text analysis over user reviews on a website for a beginner? [closed]

I want to analyse user reviews for certain products as part of a research project without having to learn analytics from scratch, as my requirement is temporary. I need to do the following: The user ...
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Where can I learn the complete mathematics involved in LDA?

I have come across Latent Dirichlet Allocation (LDA) on multiple occasions while reading about sentiment analysis and recommender systems. Where can I find good reading material which explains the ...
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LDA for sentiment analysis

As far as I understand it, LDA works by assuming that a corpus was written by a set of topics ands words corresponding to that topic by a specific distribution. I'm however not enterely sure what the ...
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21 views

Why using a frozen embedding layer in an LSTM model

I'm studying this LSTM mode: https://www.kaggle.com/paoloripamonti/twitter-sentiment-analysis They use a frozen embedding layer which uses an predefined matrix with for each word a 300 dim vector ...
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Training on heterogeneous dataset for sentiment analysis

I have a dataset of wine reviews, the dataset is consisted of wine reviews(text representation) and other features as score, age, flavors... Wherever the wine is good or not, a score(target) from 0 to ...
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How to label a dataset for Machine Learning?

I have a collection of educational dataset. The dataset consists of a username and their review for the course. I want to analyze the data for sentiment analysis. How can I label the data to train ...
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LSTM input and output for sentiment analysis

I'm studying this LSTM network: https://www.kaggle.com/paoloripamonti/twitter-sentiment-analysis ...
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CNN accuracy and loss doesn't change over epochs for sentiment analysis

I am performing text classification as Good [1] or Bad [0]. The texts are preprocessed and converted to Vectors using Google Word2Vec. Further CNN architecture is used for training. I have roughly ...
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What kind of test should I use to determine correlation between the value of a commodity and consumer sentiment?

I’m currently studying data science and am trying to apply my skills to a small project. Basically, I’ve collected data about a commodity’s value over two time periods (30 data points each in 4 week ...
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TDIF toarray() returns an array of zeros

radius = tvec.fit_transform(test_df.Tweet_lemmatized) c = tvec.get_feature_names() print(radius) This returns the correct values, but when I try to convert it to ...
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Sentiment Analysis Datasets

I am looking for sentiment analysis data, mostly customer product review. I found a lot of research places provide large size of datasets, but many of them are outdated. I want to get more up-to-date ...
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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 ...
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prepare email text for nlp (sentiment analysis)

I have text of emails, which also contains disclaimers, phone numbers, email addresses, file attachment names, addresses, greetings etc. At the moment I blindly pass this text through an OOTB ...
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124 views

Confidence Score For Trained Sentiment Analyser Model

I have trained a text based sentiment analysis model, using SciKit-learn and custom data. I have the model ready and it works fine in predicting a text to a class (Positive or Negative or Neutral). I ...
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Sentiment analysis with nltk

I'm studying sentimental analysis with python library nltk, following this example: ...
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Weights initialization in Neural Network

I was viewing code for custom neural network for sentiment analysis. It had 3 layers (1 hidden layer). I am more concerned with weight initialization for the layers ...
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Kmeans cluster validation when I have labeled test data

I'm trying to implement the unsupervised k-means algorithm for sentiment analysis of imdb movie dataset created by stanford. The steps that I followed is : 1) Load the comments 2) Apply tokenization ...
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How dictionary is created when making dictionary-based text classifications? How accuracy of values are determined?

I'm trying to create sentimental analysis of about 1 million twits I've collected from Twitter. I've found a lot of dictionary related to text categorization. The dictionaries I found were rated words ...
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Sentiment analysis for multiple entry in one text

I would like to do sentiment analysis on a set of financial news from the S&P 500 for given entities (organization names). However, each news (rows in my dataset) may have more than one entity and ...
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42 views

long short term memory in sentiment analysis

I am trying to understand how can long short term memory be used in detecting emotions in dialogues. I would like to know if there are some good tutorials for beginners that I can follow. I watched a ...
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Sentiment Analysis Naive Bayes vs Logistic Regression [closed]

I am doing some sentiment analysis on Twitter data, and I wanted to compare a Naive Bayes Classifier and a Logistic Regression classifier as to if their performance is affected by spell checking the ...
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167 views

On a multi lingual sentiment corpus

I am looking to compile a sentiment corpus for news articles in multiple languages (~100k per lang. for a machine learning experiment) where each article is labeled positive, neutral, or negative. I ...
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any efficient way to find surrounding adjective/verbs with respect to the target phrase in python [updated]?

I am doing sentiment analysis on given documents. My goal is to find out the closest or surrounding adjective words with respect to the target phrase in my sentences. I do have an idea how to extract ...
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Visualising a stream of emotions

I have a stream of emotions (from some audio recordings) extracted by a speech emotion recogniser. My questions now are how to best display these emotions to the end users? What is the best way to ...
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39 views

Sentimental Analysis on Twitter Data [closed]

What are best ways to perform sentimental analysis on Twitter Data which I dont have labels for?
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219 views

Why do we have to remove most common words for text analysis?

I am trying to do sentiment analysis the task is to classify racist tweets from other tweets. And I have read many articles and many have mentioned to remove the most common 10 words from the column ...
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What is parts of speech technique in sentiment analysis?

In an article, I saw Sentiment Analysis using Parts Of Speech(POS) technique. When I searched I got some paper on POS but I couldn't understand what POS basically is. Though I am new to sentiment ...
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101 views

Integration of Sentiment analysis in CRM

What is the process for integrating sentiment analysis in a CRM? What I am searching for is a system which analyzes the customer comments or reviews using the CRM and finds out the customer sentiment ...
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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 ...
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NLP - How to perform semantic analysis?

I'd like to perform a textual/sentiment analysis. I was able to analyse samples with 3 labels: (positive, neutral, negative) and I used algorithms such as SVM, ...
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Most Efficient Machine Learning Algorithm for Text Analysis

Looking at Understanding Convolutional Neural Networks for NLP, Convolutional Neural Networks (CNNs) seem to be suitable not only for image recognition, but also for NLP. Are CNNs in general the best ...
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229 views

Algorithms for Sentiment Analysis on Entity

I want to make sentiment analysis for an entity which was found, like Google NLP. Entity should have magnitude and score. Please share with me the possible research papers. p/s please not propose ...
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83 views

what is the reason behind the bad outputs gained by RNN, LSTM when using GloVe pretrained model in text classification?

the problem is with the results gained for accuracy and f1 afer training our model via pretrained models such as GloVe. when I apply CNN as a classifier, the result are good as follows: ...
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490 views

how to input the data set in to a word2vec by keras?

I am new in using word2vec model, as a result, I do not know how I can prepare my dataset as an input for word2vec? I have searched a lot but the datasets in tutorials were in CSV format or just one ...
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1answer
1k views

Why TF-IDF is working with Sentiment Analysis?

Word2vec looks excellent to me as representation of corpus for sentiment analysis. It has relations between words etc. TF-IDF has only weight of the word how important it is. Results with sentiment ...
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319 views

transfer learning with sentiment analysis?

The question is how good and what are some things to keep in mind when sentiment analysis models are tested on different datasets than they are trained on. Say the task is to perform sentiment ...
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468 views

Naive Bayes for SA in Scikit Learn - how does it work

Okay so i scrape data from the web on movie reviews. I also have already got my own 'dictionary' or 'lexicon' with words and their labels (1-poor, 2-ok, 3-good, 4-very good, 5-excellent). SO the ...
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19 views

how to augument speech sentiment dataset?

I am building an LSTM to recognize if the person is sad, happy, angry or neutral. This is done by feeding-in his the wave of his voice into the network, as a sequence of bytes (each byte is 0-to-255). ...
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Are there trained neural networks, that can distinguish a book's author point from what he stands against?

Let's take some specific book to narrow this example. Atlas shrugged by Ayn Rand. When i'll be saying something like "Ayn Rand's ideas", i'll mean only those, which are clearly stated in the book. ...
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Method of data collection [closed]

I am an undergraduate that is currently working on a project in which I need to collect reviews and comments about mobile phones across several platforms and analyse the data to see if the sentiments ...
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42 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 ...
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Related words extraction in text processing

I'm working on some aspcet based sentiment analysis project applied on some tweets or reviews, so far I've applied all the known preprocessing methods on my training dataset which is an XML file that ...
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265 views

How to combine sparse text features with user smile for sentiment classification? [closed]

I am trying to perform sentiment classification task where I have some text and some information about whether the user smiled or not. Now when I use count-vectorizer to convert my text to feature ...