The tag has no wiki summary.

learn more… | top users | synonyms

0
votes
0answers
52 views

How to validate sentiment classification and compare different algorithms

I need to compare SVM and NB about sentiment classification by evaluating accuracy, precision and recall measures. I have 1500 manually classified documents, and I would know which is the best way to ...
1
vote
0answers
41 views

Maximum Entropy classifier, high precision but low recall

I'm working on a sentiment analysis study of twitter data using the Maximum Entropy classifier. I've gathered dozens of thousands of tweets. To produce features, I used unigram, bigram and dictionary. ...
2
votes
1answer
69 views

How to prepare a dataset for text classification

I would like to compare some algorithms for performing sentiment classification (Naive Bayes, SVM, and ...
2
votes
0answers
72 views

Has the reported state-of-the-art performance of using paragraph vectors for sentiment analysis been replicated?

I was impressed by the results in the ICML 2014 paper "Distributed Representations of Sentences and Documents" by Le and Mikolov. The technique they describe, called "paragraph vectors", learns ...
1
vote
0answers
37 views

Power Analysis for Text Mining

I have a population of 6 million text files with which I want to perform sentiment analysis (and text analysis more generally). I will need to manually hand code a subset of these texts into positive ...
1
vote
1answer
176 views

Analysis of Customer satisfaction surveys

I have customer feedback data about 2-3 products from 100 customers. Number of questions are around 160. I have data in excel format. Header row contains the question and row below contains the ...
0
votes
0answers
47 views

NaiveBayesClassifier vs SklearnClassifier

I'm using both nltk NaiveBayesClassifier and SklearnClassifier for classification of sentences. Is there is a way to find which is the best classification. For eg: If i give "You are looking not so ...
0
votes
0answers
28 views

How to test if the mean of data collected over many days is significantly higher on a predicted day

I have some data examining blog posts on different days. Basically, about 2000 news articles pertaining a certain topic were sampled and each blog post was given a positivity percentage score ...
1
vote
0answers
254 views

Sentimental Analysis using Naive Bayes

I am working on problem solution where I am collecting social feeds from twitter and Facebook for a product X . I am labeling these posts,comments or tweets using five labels ...
1
vote
0answers
29 views

How do I get sentiment from a certain “perspective” or point-of-view?

Consider the following text The verdict is out, the jury has held MS guilty of infringements and levied penalties aggregating to $1.50Bn. It will be a massive blow to the reputation of MS. The ...
1
vote
1answer
112 views

Sentiment Analysis with respect to subject

I'm familiar with the bag of words/Naive bayes sentiment analysis for text (e.g. http://streamhacker.com/2010/05/10/text-classification-sentiment-analysis-naive-bayes-classifier/) I was curious to ...
1
vote
0answers
115 views

Using sentiment lexicons or all words processing for sentiment analysis?

I am learning sentiment analysis to apply it to twitter real time data to predict user's mood. I ponder about using which alternative way to do that data mining job. Use all words to process and ...
6
votes
2answers
1k views

Supervised approaches vs. topic models in sentiment analysis

I am researching Sentiment Analysis over social media, particularly classifying online texts such as blog posts as positive, negative or neutral. Most of the approaches I have found for sentiment ...
7
votes
2answers
344 views

Understanding and applying sentiment analysis

I was just having been assigned a project of conducting sentiment analysis for some document collections. By Googling, a lot of sentiment-related research has popped up. My questions are: What are ...
6
votes
0answers
738 views

Maximum entropy classifier and sentiment analysis

I am doing a project work in sentiment analysis (on Twitter data) using machine learning approach. In order to find the 'best' way to this I have experimented with naive Bayesian and maximum entropy ...