Survey results, social media mentions and product reviews can be identified, classified and deciphered automatically through text analysis software.
Text analysis is a procedure based on the use of computer systems for the exploration, reading and interpretation of written content or unstructured data. The idea, within the framework of this automated process that replaces human action by making use of some benefits of artificial intelligence , is to obtain information of corporate relevance extracted from social network publications, emails , product reviews , documents, etc.
By appealing to natural language processing (NLP) and machine learning algorithms, efficient operation of text analysis software is achieved, making the program capable of associating certain terms with specific meanings and managing to carry out a semantic analysis of unstructured data. . Knowing how to use and decipher the results of text analysis leads to smarter and more advantageous business decisions.
Text analysis , experts in this field indicate, requires the orderly completion of a series of stages that begin with a collection or selection of internal and external data. Then they must be prepared in a suitable format so that the system can analyze them: here tokenization , grammatical tagging (POS tagging) , syntactic analysis , lemmatization and the removal of stop words take center stage. The next step is, precisely, the processing of the content using procedures such as text classification and extractions . Finally comes the visualization stage , a phase that adapts the results to a format that is clear and simple.
Types of text analysis
There are different types of text analysis , as well as multiple techniques covered in this matter, which involves tracking an immense amount of content and establishing trends, patterns and updated panoramas.
One of the modalities is known as sentiment analysis and it is a great resource to automatically retrieve relevant information regarding the level of satisfaction, reactions and opinions of a company's customers.
It is usual to take into account, on the other hand, frequency analysis , useful to identify the words that are most repeated and evaluate the impact of each one.
Topic modeling also serves to distinguish consumer sensations or verdicts, while named entity extraction is of great help for the identification and categorization of key information items within unstructured texts.
Hand in hand with artificial intelligence it is possible to benefit at a corporate level with deductions, interpretations and analysis of unstructured data.
Key concepts
In addition to the notions mentioned above, there are other key concepts that are related to the process of text analysis .
One of the expressions that is very popular in the field of text analysis derives from the field of data mining and is defined as text mining . It is an ideal tool to, based on correlations and patterns between words, discover data that is not explicitly marked in the general content.
For cybersecurity purposes, to add more details in this regard, there are those who, when developing programming tasks or engaging in computer activities, use a technique called stemming to eradicate and replace suffixes from the roots of words.
Nor can we fail to mention optical character recognition (OCR) , as described as a process that is based on the conversion of a certain text image into a format that machines can recognize and assimilate for reading. Thanks to this option, when scanning a receipt, voucher or form, the computer can save that document as an image file .
Thanks to text analysis, data of business interest is collected, user reactions and opinions are identified and, based on this information, favorable corporate decisions can be made in real time.
Text Analysis Examples
By deepening knowledge about what text analysis is and what it consists of, examples of use and exploitation emerge from practice.
The QServus management platform, to indicate a specific case, allows companies to know what and how their customers' experience is (through personalized surveys and scale questions designed to determine user loyalty, among others) in order to power, in real time, to promote continuous improvement actions.
The QuestionPro app, meanwhile, opens the possibility of launching surveys on mobile devices (with Android or iOS operating system) even when there is no Internet connection. By using QuestionPro Text Analysis , in particular, you get constantly updated reports, sentiment analysis , and topic extraction .
The Lexalytics platform also accumulates good recommendations, which captivates many users for providing integration with multiple business applications, being very precise when carrying out sentiment analysis , and for its multilingual support.
Another modern alternative to consider is MonkeyLearn , a software that surprises with its benefits thanks to machine learning . As points in its favor, it is recognized for its affordable price, its versatility in relation to actions typical of text analysis and its simple interface.