Text Mining in Big Data Analytics

Text mining in big data analytics is emerging as a powerful tool for harnessing the power of unstructured textual data by analyzing it to extract new knowledge and to identify significant patterns and correlations hidden in the data. This study seeks to determine the state of text mining research by...

Full description

Saved in:
Bibliographic Details
Published in:Big data and cognitive computing 2020-03, Vol.4 (1), p.1
Main Authors: Hassani, Hossein, Beneki, Christina, Unger, Stephan, Mazinani, Maedeh Taj, Yeganegi, Mohammad Reza
Format: Article
Language:English
Subjects:
Analysis
analytics
Big data
Data mining
Methods
review
Social media
text mining
Text processing
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Text mining in big data analytics is emerging as a powerful tool for harnessing the power of unstructured textual data by analyzing it to extract new knowledge and to identify significant patterns and correlations hidden in the data. This study seeks to determine the state of text mining research by examining the developments within published literature over past years and provide valuable insights for practitioners and researchers on the predominant trends, methods, and applications of text mining research. In accordance with this, more than 200 academic journal articles on the subject are included and discussed in this review; the state-of-the-art text mining approaches and techniques used for analyzing transcripts and speeches, meeting transcripts, and academic journal articles, as well as websites, emails, blogs, and social media platforms, across a broad range of application areas are also investigated. Additionally, the benefits and challenges related to text mining are also briefly outlined.
ISSN:2504-2289
2504-2289
DOI:10.3390/bdcc4010001