As you explicitly ask for comparisons, here is a comparison of different techniques,

X. Zhang and X. Zheng, "Comparison of Text Sentiment Analysis Based on Machine Learning," 2016 15th International Symposium on Parallel and Distributed Computing (ISPDC), 2016, pp. 230-233, doi: 10.1109/ISPDC.2016.39.

compare a Support Vector Machine with Extreme Learning Machine. A nice preparation utilising particle swarm optimisation is found here:

I. Kurniawati and H. F. Pardede, "Hybrid Method of Information Gain and Particle Swarm Optimization for Selection of Features of SVM-Based Sentiment Analysis," 2018 International Conference on Information Technology Systems and Innovation (ICITSI), 2018, pp. 1-5, doi: 10.1109/ICITSI.2018.8695953.

A work available here on Researchgate, discussing Extreme Learning Machines is

Article An Empirical Study of the Extreme Learning Machine for Twitt...

I hope you find it helpful, greets

Marcus

Dear Matt Jans

I suggest these articles, have a look:

1. Article Systematic reviews in sentiment analysis: a tertiary study

2. https://www.sciencedirect.com/science/article/pii/S2090447914000550

3. Article A Review on Sentiment Analysis Approaches

4. https://journalofbigdata.springeropen.com/articles/10.1186/s40537-015-0015-2

Kind Regards

Qamar Ul Islam

1. A comprehensive survey on sentiment analysis: Approaches, challenges and trends

https://www.sciencedirect.com/science/article/abs/pii/S095070512100397X

2. Sentiment analysis using deep learning architectures: a review

Article Sentiment analysis using deep learning architectures: a review

3. Opinion Mining and Information Fusion: A survey

https://www.sciencedirect.com/science/article/abs/pii/S1566253515000536

4. A review of natural language processing techniques for opinion mining systems

https://www.sciencedirect.com/science/article/abs/pii/S1566253516301117

Thanks everyone! This is really helpful. Just to show you that I'm not just a taker, here's one I found that was helpful. Will share the other once I have a chance to review.

van Atteveldt, W., van der Velden, M. A. C. G., & Boukes, M. (2021). The Validity of Sentiment Analysis: Comparing Manual Annotation, Crowd-Coding, Dictionary Approaches, and Machine Learning Algorithms. Communication Methods and Measures, 15(2), 121–140. https://doi.org/10.1080/19312458.2020.1869198

Article The Validity of Sentiment Analysis: Comparing Manual Annotat...

Are you just wanting a feedback on a survey you have given from three choices then a simple value to each of the three choices, if this is all then I suggest a small program written in simple code giving an end, I am out of the loop for purchasesble apps, back in the day I would have rattled something on my own for the task, it was DCL I programmed in, the lexical functions where notable.

Is there anyone here that could rattle you up something that you could feed the raw data into a spread sheet then create a chart,

If there are not too many surveys to run, it might be beneficial to use human ingenuity, a human for the full task of collating and conglomerating/tabulating the results

It may actually be faster also instead of using an app you will have to train a staff member or yourself

Interesting, I will research these answers

Might I interject, to err is human, but attempting to understand someone else's gui to fit into your specific needs is not always beneficial to the easy facilitation of the end result required

How many in the survey

https://www.cs.uic.edu/~liub/

Hi Matt Jans . See the link: https://liris.cnrs.fr/Documents/Liris-6508.pdf

See the following link: https://homepages.dcc.ufmg.br/~fabricio/download/cosn127-goncalves.pdf

Also see the following link: https://towardsdatascience.com/sentiment-analysis-comparing-3-common-approaches-naive-bayes-lstm-and-vader-ab561f834f89

Kindly see also the following RG link: Conference Paper Comparing and combining sentiment analysis methods