Comparative Sentiment Analysis and Semantic Meaning in Text using sentiment models from Hugging Face and Power Automate

Trajkovska, Aneta and Jolevski, Ilija Comparative Sentiment Analysis and Semantic Meaning in Text using sentiment models from Hugging Face and Power Automate. In: XVI INTERNATIONAL CONFERENCE ETAI 2024, 21 – 23 September 2024, Struga, North Macedonia.

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Abstract

This paper outlines an innovative approach
utilizing Artificial Intelligence models for determining the
semantic meaning of sentences. In linguistics, it is crucial to
understand how we interpret texts and uncover the underlying
messages conveyed by the authors through their sentences.
Today, we are witnessing significant advancements in technology
and decision-making, driven by previous experiences, diverse
databases and knowledge systems. This wealth of data is
processed using various robotic systems and artificial intelligence
models. Large corporations often receive extensive customer
reviews and feedback on their products, but manual reading and
analysis can be challenging. In this article we will show how
utilization of the Hugging Face models and Power Automate
models can do deeply semantic analysis on text and how the
punctuation marks can impact the way how the text is written
and the whole meaning. Hugging Face can assist by using its
advanced natural language processing models to automatically
analyze and interpret extensive customer reviews and feedback,
streamlining the process. Power Automate can help by
automating the collection, organization, and initial analysis of
customer reviews and feedback, reducing the manual workload.
The synergy between both technologies will be described, as well
as their powerful utilization to explore a range of innovative
applications to showcase their versatility and practicality.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Scientific Fields (Frascati) > Natural sciences > Computer and information sciences
Divisions:	Faculty of Information and Communication Technologies
Depositing User:	Prof. d-r. Andrijana Bocevska
Date Deposited:	16 Dec 2024 07:52
Last Modified:	16 Dec 2024 07:52
URI:	https://eprints.uklo.edu.mk/id/eprint/10543

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