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The story behind the data: How text analytics is changing the game for business intelligence?
In today's data-driven era, how companies collect, analyze and utilize information is crucial. Among them, "text analysis", as a brand-new technology, is gradually changing the way business intelligence operates. Text analysis, also known as text mining, aims to extract high-quality information from written materials and through this process, reveal the hidden stories behind the data.
Text analysis involves discovering new knowledge through computers, by automatically extracting information from a variety of written sources, which can include websites, books, emails, reviews, and articles.
Based on this process, text analysis has a wide range of applications. Ronen Feldman modified the term "text mining" in 2004 and proposed the more commonly used term "text analysis" today, emphasizing its importance in a business environment. According to surveys, about 80% of business-related information exists in unstructured form, mainly text, which is where text analysis comes into play.
The process of text analysis
The process of text analysis usually includes several subtasks, such as:
- Dimensionality reduction processing: used to identify the roots of words and reduce the size of text data.
- Information retrieval: Collecting or identifying a set of textual material to be analyzed.
- Named entity recognition: Use lexicon or statistical techniques to identify named entities in text.
- Document clustering: Identify a group of similar text documents.
- Sentiment analysis: Analyze the subjective material in the text to extract information such as mood and emotion.
These techniques and processes enable the discovery and presentation of knowledge, facts, business rules, and relationships that are often hidden in text.
Applications of text analysis
Text mining technology is widely used in government, scientific research and business fields. Legal professionals may use it for electronic discovery, and governments and the military use it for national security and intelligence analysis. In addition, scientific researchers utilize text mining methods to organize large-scale text data.
In the business world, text analysis is used to support various activities such as competitive intelligence and automated advertising.
Safety and biomedical applications
Text analysis is also widely used in security applications, especially in monitoring and analyzing online textual materials, such as Internet news and blog posts. Applications in the biomedical field For example, text mining methods are used to analyze literature related to protein interactions and disease associations.
Business and Market Application
In enterprises, text analysis is widely used in customer relationship management. For example, Coussement and Van den Poel used text analytics to improve customer churn prediction models in their 2008 study. It is also used to predict stock returns and evaluate market sentiment for products.
Sentiment analysis can help businesses understand customer needs and emotions, and then develop more effective market strategies.
Legal considerations for text analysis
However, the development of text analysis has not always been smooth sailing. As technology evolves, legal regulations on text mining in some areas also change. Taking Europe and the United States as examples, text mining is considered legal under the "fair use" regulations in the United States, but in Europe there are more restrictions, including copyright considerations.
Future Outlook
With the advancement of artificial intelligence technology, text analysis will continue to evolve in the future and realize its potential in a wider range of fields. Text analysis is not only the organization of data, but also the in-depth exploration and understanding of information. This will not only enhance the wisdom of corporate decision-making, but also add a new dimension to academic research.
In this era of information explosion, are you also thinking about how to use text analysis to gain insight into your business world?
