Text Analysis

A technique in which text is analyzed and converted into data pieces that machines can understand to derive important results.

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What is Text Analysis?

Text analysis (also known as Text Mining or Content Analysis) is a technique that computers use to extract worthwhile information from the human language in a smart and efficient manner. Researchers and developers can use this method to assemble diverse and unorganized data in a structured form. In this process, documents are disintegrated for hassle-free management of data pieces, simply put: unstructured text gets converted into structured data.

Once the sentences are put to paper, the integral sections such as the proper nouns are branched off using the list of words in the dictionary. The analysis of text, those in either documents or graphics, qualitative details can be transformed into quantitative details. It’s safe to establish text analysis is a research approach adapted to put together reasonable conclusions by decoding the content.

Developers and researchers use text analysis for establishing correlation between two entities, automated summary generation, translation, speech recognition and other similar content management tasks that come their way. If we talk about the business aspect, text analysis offers many wider subjects such as semantic search and content management to gather information.

Text Analysis Techniques

Conduct quicker qualitative market research and quantitative market research by implementing text analysis as it emphasizes all the important terms and categorizes the responses for open-ended questions in particular.

For survey makers, it’s crucial to analyze the responses received for their surveys and analyzes of the open-ended responses can be done using text analysis. A text analysis software will be useful to organizations who want their unstructured data to get structured by observing patterns in the text and converting data into computer-readable formats. Text analysis software for sentiment analysis or linguistic analysis or quantitative text analysis can be used to convert text into practical information that can be influential in making smart decisions for the business.

Thousands of valuable data received through surveys or any other medium can be analyzed using these text analysis techniques. The first step in this retrieval and analysis process is to identify textual information over the internet or on the files in the computer system or database.

Text Analysis Examples

Text analysis is a fairly new concept in the computer science that involves making huge quantities of unorganized data congenial and constructive. This helps in increasing value of the data as well as elevating this data can be used in risk management or paths such as cybercrime.

Here are 5 text analysis examples to create awareness about the applications of text mining in today’s world:

  1. Prevention of cyber crimes:Due to the nature of how the internet operates, it’s a highly vulnerable medium for data sharing and communication. This has opened doors for a lot of unforeseen cyber crimes which can be prevented using text analysis. It’s probably one of the very few techniques being used to prevent cyber crimes.
  2. Efficient customer service:This is one of the basic examples of text analysis which caters to improving customer service using mediums such as survey software or customer satisfaction calls to make better products or services. This technique helps in building customer trust by providing quick and automated responses to them in times when they need assistance. This happens as their dependence on operators reduces drastically and saves them a lot of time.
  3. Advertising via digital mediums:These days, advertising firms rely on digital mediums to gather reliable results. Text analysis is one of the most critical tools that advertising firms use to obtain precise 360-degree results. In comparison to traditional advertising methods such as the cookie-based approaches, it has an edge in terms of the secured privacy it offers along with accurate results.
  4. Enhance your content:Content generation relies on human effort but it eases the process of content creation as far as managing the sizeable bulk of data is concerned. Using text analysis, content can be enhanced by added multiple aspects such as organizing or giving the content an outline to make it applicable to more than one implementations.
  5. Data analysis for social media networks:Social media is the most effective mediums to get in touch with your target audience to get feedback, reviews, and criticism to improve and also gives access to a pool of data. Companies are developing social media strategies to get insights about their product performances and to also understand the buyer’s persona so that making improvements can have a defined path. That’s where text analysis comes in. It makes analyzing humongous amount data, deriving results from the analysis and also understanding user feedback and emotions easier to implement.

The implementation of a software is just the start of the entire process of utilizing data. A large amount of data is analyzed and the result of this analysis is entered into sheets which are then scanned for observing data patterns, to offer systematic closure to the text, use the retrieved information to make the text better and avoid restricting yourself to keywords.

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