Text mining or information discovery is that sub manner of information mining that is extensively being used to find out hidden styles and huge records from the massive amount of unstructured written fabric. Text mining allows accelerate know-how discovery by way of notably growing the amount records that can be analyzed. Rapid development in digital facts acquisition strategies have caused huge extent of facts. More than 80 percentages of these day’s statistics is composed of unstructured or semi-based information. This sort of data cannot be used until or unless particular records or pattern is determined. The discovery of appropriate patterns and trends to research the text documents from large quantity of records is a big issue. Social community applications create possibilities to set up interaction amongst people main reciprocal studying and exchanging of relevant understanding, chat, feedback, and discussion forums. Information in social media web sites is disorganized and fuzzy in character. In normal lifestyles conversations, people does not care about the spellings and correct grammatical creation of a sentence that could result in exceptional styles of ambivalence, such as syntactic, lexical and semantic. Large quantities of unstructured text information generated on the Internet, text mining is thought to have excessive business fee. We describe how textual content mining might also expand modern organizational studies with the aid of permitting the testing of present or new research questions with information which are likely to be rich.
Padhi, Gopal Krushna and Tripathy, Sushreeta
"Application of Text Mining in Social Media,"
Graduate Research in Engineering and Technology (GRET): Vol. 1:
6, Article 3.
Available at: https://www.interscience.in/gret/vol1/iss6/3