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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14 views

Further Classification by function [closed]

I am a bit confuse and stuck at a problem, may be someone can guide me in right direction I am doing an analysis and have 3 datasets, supporting, against and neutral, or in simple say negative, ...
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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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A question with concatenating data

Quite new to deep learning. I'm attempting to use sentiment analysis to examine some word input along with a network to examine some sequential data. I've seen some examples of sentiment analysis, ...
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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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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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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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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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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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How to calculate personality scores using a machine learning approach?

I am interested to calculate personality scores using a text analysis approach. As I read it is better to use a machine learning supervised learning approach in combination possible with a dictionary ...
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220 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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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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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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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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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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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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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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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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Where can I get an untokenized version of GLUE's SST-2 dataset?

On the GLUE faq, they say: Similarly, for SST, the data provided is already tokenized. We're working on obtaining a version that is not tokenized. Feel free to train on other distributions of ...
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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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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 ...
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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 ...
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Approach for sentiment analysis of Flemish Twitter data (politics)

I have collected about 280.000 tweets posted by Flemish (Dutch) people concerning the previous elections. I used the twitter API and filtered for mentions of know political parties and politicians. ...
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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 ...
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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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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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217 views

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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240 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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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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58 views

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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344 views

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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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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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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346 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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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 ...