Please refer any website/ Paper/ Tutorial/ Link where text mining analysis is being used with conclusion formulation.
You may read
http://ijarcce.com/upload/june/6-A%20tutorial%20review%20on%20Text%20Mining%20Algorithms.pdf
Text analytic is the process of analyzing unstructured text, extracting relevant information, and transforming it into useful business intelligence.
steps for Text analytics
https://www.google.co.in/search?q=text+analytics&espv=2&biw=1242&bih=607&tbm=isch&tbo=u&source=univ&sa=X&ved=0ahUKEwiD5ITejovLAhWKkI4KHTQlDzUQsAQIYQ#imgrc=q6ChrCubPi4euM%3A
You can use WEKA software. See the below link:
http://www.cs.waikato.ac.nz/ml/weka/
Text Analytic is the process of exploring the hidden features in the text data. This field is becoming more popular because of unstructured data is generating rapidly from the various sources micro-blogs, social media, forum, e-commerce and blogs.
using various tools insights of the text can be identified.
Popular tools are Weka, R, RapidMiner and Knime.
Just an example you can refer to this book for knowing what kind of analysis can be found in text minig
"Text Analysis with R for Students of Literature"
If you want to try out some data collection for yourself Inrecommend DiscoverText and Sifter. You can use DiscoverText (https://discovertext.com) for real time Twitter and some Facebook data. You can use Sifter (https://sifter.texifter.com) for historical Twitter data.
Realtime data collection using the Twitter Search API and the Gnip PowerTrack 2.0 is available using a point and click (no programming) interface at https://discovertext.com. Here are the top 10 reasons to use DiscoverText:
https://vimeo.com/170157685
For three free historical Twitter data estimates per day, create a free account on Sifter (https://sifter.texifter.com).
I have found DiscoverText to be a really accessible platform that is easy to use — hope this helps!
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