If you're aware of Standford NLP, it has an web based interface:

https://corenlp.run/

A tool which meets all requirements is not known to me. However, it is possible to combine known elements based on Python and to build a web interface to combine them. In our paper, which you can download for free from IEEE Xplore, we have made a relatively precise suggestion concerning the building blocks. Article The Application of Artificial Intelligence Technologies as a...

Hi,

Kindly Refer:

http://www.sthda.com/english/wiki/text-mining-and-word-cloud-fundamentals-in-r-5-simple-steps-you-should-know

Best Wishes..

Hi,

1. Stopwords, you can import the nltk package from python

import nltk

stopwords = nltk.corpus.stopwords.words('english')

2. stemming, you can also use nltk package

from nltk.stem.porter import * stemmer = PorterStemmer()

wordAfterStemmer = stemmer.stem(word)

3. word cloud, you may use d3.js to draw the word cloud

4. topic modeling, you may use "gensim" to run the lda algorithm

https://towardsdatascience.com/topic-modeling-and-latent-dirichlet-allocation-in-python-9bf156893c24 , please refer to this web page for LDA

You might consider taking a look at Linguistic Inquiry and Word Count (LIWC) that can be found at http://liwc.wpengine.com/

This is a commercial product but I see that they have an option for academic licenses.

There are a number of YouTube tutorials that show you how to start using it that might be helpful such as this one

https://www.youtube.com/watch?v=ACpyHgQs0Ew

best of luck

John

Hi,

you can using this tool

https://www.cs.waikato.ac.nz/ml/weka/

Regards

GATE (General Architecture for Text Engineering) is an on line open source software toolkit. It supports the main NLP and machine learning tasks (classification, regression, tagging, topic models, text mining, ...):

https://gate.ac.uk/

https://gatenlp.github.io/gateplugin-LearningFramework/

You can try using MALLET, that was developed at UMASS Amherst. In addition to topic modelling, the tool allows you to perform decision tree analysis, sequence tagging, regression, etc.). Removing stop words, stemming, and optimization are done together.

http://mallet.cs.umass.edu/topics.php

McCallum, Andrew Kachites. "MALLET: A Machine Learning for Language Toolkit." http://mallet.cs.umass.edu. 2002.

The OP asked for an Online (web-based) tool, most of the answers seem to be neglecting the point.