0

I am looking for a sentiment dictionary/lexicon for business context to perform sentiment analysis. I have already built the analysis and calculation portion, but simply need the classes with contents.

Here's an example of what I want to build on:

PositiveWords = ['good', 'return','up']
NegativeWords = ['bad','disappointing','dropped']

I am looking to populate these lists further but only for words used when talking about stock performance of a company.

Thanks! Ryan

Ryan Clark
  • 1
  • 1
  • How are you doing the calculations? There are a lot of resources for how to do this in python, but they generally involve machine learning. For example, there are libraries that are able to encode the overall sentiment of words, but I don't think the way they work is especially useful if you're just getting lists of good and bad words. – LTheriault Mar 12 '20 at 14:47
  • Its a very simple calculation (currently learning python and use this as an application for some basic functions) that counts the number of positive words found in an article and compares it to negative words and total count of words. I know I am missing the mark on identifying phrases but want to move in that direction once I get this down. – Ryan Clark Mar 12 '20 at 15:08
  • Check out this link: https://medium.com/@datamonsters/sentiment-analysis-tools-overview-part-1-positive-and-negative-words-databases-ae35431a470c I haven't looked in depth, but it looks like it has the kinds of lists you're looking for. – LTheriault Mar 12 '20 at 15:11
  • Thank you! It does look like what I wanted – Ryan Clark Mar 12 '20 at 15:13

0 Answers0