Sentiment analysis with keyword extraction

Lately we have been getting a lot requests to our sentiment classifier, many are from social media analyst companies. In fact our sentiment analysis is now the most popular classifier at uClassify!

I just wanted to share something that could be usable for you guys. By using our latest Api call, ‘classifyKeywords’ you can see which keywords are the strongest triggers for the positive and negative classes. This could reveal additional valuable information for your clients.

For example, if you use the keyword analysis on a long product review, you could use the keywords to extract the sentences where the product is mentioned in a positive or negative way. Why not highlight it in green or red? Highlighting sentences will give a very good overview for human reviewers.

Here is how an XML request looks like (just swap ‘classify’ for ‘classifyKeywords’):

<?xml version=”1.0″ encoding=”utf-8″ ?>
<uclassify xmlns=”” version=”1.01″>
<textBase64 id=”tweet1″>bm93IHNvbWV0aW1lcyBpIHdvbmRlciB3aGF0</textBase64>
<readCalls readApiKey=”YOUR_READ_API_KEY_HERE”>
<classifyKeywords id=”ClassifyKeywords” username=”uClassify” classifierName=”Sentiment” textId=”tweet1″/>

You can find more info about ‘classifyKeywords’ here.

The sentiment classifier is described in more detail here.