How can I change this function to make it more efficient? I keep getting MemoryError def vectorize_sequences(sequences, dimension=10000): results = np.zeros((len(sequences), dimension)) for i, s...

first time posting a question so go easy on me. I found some code online that i am trying to implement myself though i keep coming across this error ValueError: not enough values to unpack (expec...

how does TextBlob calculate an empirical value for the sentiment polarity. I have used naive bayes but it just predicts whether it is positive or negative. How could I calculate a value for the sen...

I would like to add words to the vader_lexicon.txt to specify polarity scores to a word. What is the right way to do so? I saw this file in AppData\Roaming\nltk_data\sentiment\vader_lexicon. The f...

Trying to use Google Sentiment Analysis. Here is the code I got from the Google tutorial. """Demonstrates how to make a simple call to the Natural Language API.""" import argparse from google.cl...

I'm designing a text classifier in Python using NLTK. One of the features considered in every sentence is it's sentiment. I want to weight sentences with either positive or negative sentiments more...

I am using this example to conduct sentiment analysis of a collection of txt documents in R. The code is: library(tm) library(tidyverse) library(tidytext) library(glue) library(stringr) library(dp...

I am working on sentiment analysis and I am using dataset given in this link: http://www.cs.jhu.edu/~mdredze/datasets/sentiment/index2.html and I have divided my dataset into 50:50 ratio. 50%...

I know you can add your own words by manually adding them to the vader_lexicon.txt file. I was wondering if there was another way that you can do it in the python code as I don't want people who us...

I've been working on document level sentiment analysis since past 1 year. Document level sentiment analysis provides the sentiment of the complete document. For example - The text "Nokia is good bu...

So, this question might be a little naive, but I thought asking the friendly people of Stackoverflow wouldn't hurt. My current company has been using a third party API for NLP for a while now. We b...

Can anybody think of a way to speed up my CoreNLP Sentiment Analysis (below)? I initialize the CoreNLP pipeline once on server startup: // Initialize the CoreNLP text processing pipeline public s...

I am trying to perform sentiment analysis on the large set of data from social network. The part of the code works great with small size of data. The input size less than 20mb has no problem comp...

I am working on a R project. The data set I used is available at the following link https://www.kaggle.com/ranjitha1/hotel-reviews-city-chennai/data The code I have used is. df1 = read.csv("ch...

My text is derived from a social network, so you can imagine it's nature, I think text is clean and minimal as far as I could imagine; after performing following sanitization: no urls, no usernam...

I found this previous question on SO: N-grams: Explanation + 2 applications. The OP gave this example and asked if it was correct: Sentence: "I live in NY." word level bigrams (2 for n): "# I', "...

Is there a package or methodology in existence for the detection of flawed logical arguments in text? I was hoping for something that would work for text that is not written in an academic settin...

I am exploring tensorflow and would like to do sentiment analysis using the options available. I had a look at the following tutorial http://www.tensorflow.org/tutorials/recurrent/index.html#langua...

I want to use CoreNLP in my Android project. But when I create a CoreNLP instance like this: import java.util.Properties; import edu.stanford.nlp.ling.CoreAnnotations; import edu.stanford.nlp.neur...

I have some unlabeled microblogging posts and I want to create a sentiment analysis module. To do this I have try Stanford library and Alchemy Api web service but the result it is not very ...

Hell everyone! I'm using the Stanford Core NLP package and my goal is to perform sentiment analysis on a live-stream of tweets. Using the sentiment analysis tool as is returns a very poor analysi...

I have had a project in mind where I would download all the tweets sent to celebrities for the last one year and do a sentiment analysis on them and evaluate who had the most positive fans. Then I...

I tried naive bayes classifier and it's working very bad. SVM works a little better but still horrible. Most of the papers which i read about SVM and naive bayes with some variations(n-gram, POS et...

Am using qdap package to determine the sentiment of each review comment of a particular application. I read the review comments from a CSV file and pass it to the polarity function of qdap. Everyth...

from __future__ import division import urllib import json from math import log def hits(word1,word2=""): query = "http://ajax.googleapis.com/ajax/services/search/web?v=1.0&q=%s" if word2 ==...