Its features include:
KH Coder allows for further search and statistical analysis functions using back-end tools such as Stanford POS Tagger, the natural language processing toolkit FreeLing, Snowball stemmer, MySQL and R.
S. N. Vinithra, S.N; Arun Selvan, S.J.; Anand Kumar, M.; Soman, K.P. (2015): Simulated and Self-Sustained Classification of Twitter Data based on its Sentiment. Indian Journal of Science and Technology. Vol. 8, Issue 24 http://www.indjst.org/index.php/indjst/article/view/80205/ ↩
Public Opinion Mining on Construction Health and Safety: Latent Dirichlet Allocation Approach. Buildings 2023, 13, 927. https://doi.org/10.3390/buildings13040927 https://doi.org/10.3390/buildings13040927 ↩
Google Scholar search using Keywords "KH Coder" and "KHCoder" https://scholar.google.com/scholar?lr=lang_en&q=%22KH+Coder%22+%7C+khcoder&hl=en&as_sdt=1,5&as_vis=1 ↩
Higuchi, Koichi (2017): Scholarly research using KH Coder http://khc.sourceforge.net/en/bib.html?year=all&lang=English&key= ↩
Towler, Will (2014): Text Analytics For Everyone. UX Magazine, July 31, 2014. https://uxmag.com/articles/text-analytics-for-everyone ↩
Huirong, Cheng;Guobin, Huang; Lin, Zheng (2015): Comparison of Software for Unstructured Text Analysis:KH Coder vs. Wordstat Archived 2017-11-07 at the Wayback Machine. 图书与情报, 2015(04): 110-117. http://www.tsyqb.com/CN/abstract/abstract1528.shtml ↩