Text Mining As an Emerging Trend in Social Media

It can also be referred to as text analytics. For text data mining to be possible, it is normally advisable that the data or text on which mining is to be performed should be unstructured. Text mining Twitter can be performed on various types of text including; customer feedback, survey response, conversations, blog, documents, maintenance notes and many others.

There are a number of reasons that could make any organization decide to do text analytics on their social platforms. Below are some of these reasons discussed in detail:-

1. To uncover key Patterns in text.
   

Text analysis plays a very crucial role in pattern identification by applying the principles of Pattern matching which is an interesting discipline in computing in the field of data structures and analysis. The administrator enters the key text pattern that they need to match with from other sections of the system. Using the relevant algorithms coded into the system, the system looks for a piece of text that matches the entered text and gives feedback to the analysis personnel.

1. To better unstructured data text.
   

Unstructured data is normally in raw form and is not presentable in any way. This is because no format is put in consideration when coming up with such kind of data. Therefore text mining tries to make these unstructured data presentable through various ways. It implements statistical means of data representation such as graphs, charts and others which can be easily understood. In addition, this visual representation of data can be understood by people who are semi-literate or those who do not understand the language being used.

1. To easily understand customer requirements.
   

Normally, there is a lot of freedom on social media that allows people to convey their true feelings about a given system or product. Perhaps this is so because they have eye-conduct with the service provider. Essentially, text mining helps to trap the patterns of text that talk about user requirements of the system using the pattern matching algorithms. Therefore Text mining as a discipline is a very important tool in Social media sentiment analysis since it looks at all the data, especially user conversations and looks for matches of the key patterns that mean something close to user needs.

1. To provide answers to social media users.
   

Sometimes social media users ask some questions while using the platform. Such questions are very common and can be predicted by the system using some learning algorithms. Therefore such questions are coded in the system together with their possible answers. When users pose questions on the social site system, it performs text mining by trying to match the patterns. If the pattern match is found, then the answer is given to the user instantly. If not, the user is redirected to another page for possible solution.