I am working on a Natural Language Processing task and want to create my own corpus of some doucments. Each document has approximately 500-600 words.
Can anyone suggest how to create a corpus? As I am new to this concept of NLP.
https://www.kdnuggets.com/2017/11/building-wikipedia-text-corpus-nlp.html
Hi Sayyed,
There are online collections of texts that might be annotated (e.g.: Enron).
If you want to create a new set you can crawl documents using sets of keywords, for example.
Robert
For Rookies, you can try messing with your data with voyant-tool. Just upload your document and see what happen.
https://voyant-tools.org/
For me, NLP depends on your target. For me, I am mostly working on semantic network and frequency analysis, so tagging is not needed. But if you want to try sentiment analysis or similar things, you may need to learn R or Python.
Paul
Great help Paul. Do you have any document pertaining to this tool. It will have complete information about this wonderful tool.
I am doing this from scrap and a human-based linguistic corpus should be tailored on the task(s). It has few stages of processing the data. These could be elimination of real-world recognition marks for assuring the privacy of subjects (according to GDPR regulations), codification, annotation etc. A corpus (literal meaning was singular in Latin), in general, has a qualitative model of processing, a corpora (plural) could have a quantitative or mixed methods.
I'm also doing research on this, and I'm trying to implement a Python library model, such as Stemming English
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