Abstract
Text Classification problem has been thoroughly studied in information retrieval problems and data mining tasks. It is beneficial in multiple tasks including medical diagnose health and care department, targeted marketing, entertainment industry, and group filtering processes. A recent innovation in both data mining and natural language processing gained the attention of researchers from all over the world to develop automated systems for text classification. NLP allows categorizing documents containing different texts. A huge amount of data is generated on social media sites through social media users. Three datasets have been used for experimental purposes including the COVID-19 fake news dataset, COVID-19 English tweet dataset, and extremist-non-extremist dataset which contain news blogs, posts, and tweets related to coronavirus and hate speech. Transfer learning approaches do not experiment on COVID-19 fake news and extremist-non-extremist datasets. Therefore, the proposed work applied transfer learning classification models on both these datasets to check the performance of transfer learning models. Models are trained and evaluated on the accuracy, precision, recall, and F1-score. Heat maps are also generated for every model. In the end, future directions are proposed.
Highlights
Natural language processing is a scientific process to train a computer to understand and process human language
Researches show that NLP, data mining, and text classification can be very helpful in every prospect of life. ere are many other researchers who have used NLP in hate speech, sentiment analysis [2], detection of controversial Urdu speeches [3], movie reviews [4], stock market [5], online reviews [6], and restaurant reviews [7]
The detection was improved by half which was promising. e authors of [62] worked with DistilBERT and proposed a mechanism for answer selection and picking up important words. e performance was improved by 0.6% which is not bad at all. e authors of [63] retrained DistilBERT on universal dependencies for the purpose of a voice shopping assistant. e performance of these downstream tasks is raised by 1.31%
Summary
Natural language processing is a scientific process to train a computer to understand and process human language. NLP gained a lot of importance in recent years because of the researchers and processing powers of machines. Researchers are doing their best to generate interesting facts and figures from human language and implement those results in every field of life from educations to hospitals, industry to shopping malls, etc. Natural language processing and text mining refer to the process of human-generated text that came from multiple social media networks using different algorithms, programs, and techniques. Researches show that NLP, data mining, and text classification can be very helpful in every prospect of life. ere are many other researchers who have used NLP in hate speech, sentiment analysis [2], detection of controversial Urdu speeches [3], movie reviews [4], stock market [5], online reviews [6], and restaurant reviews [7]
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