Twitter Sentiment Analysis using Machine Learning Techniques: A Case Study of ChatGPT
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AU5X9KDEX" target="_blank" >RIV/00216208:11320/23:U5X9KDEX - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174706225&doi=10.1109%2fInC457730.2023.10262961&partnerID=40&md5=fb0c26950ae77605c354ecf080a9f81d" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174706225&doi=10.1109%2fInC457730.2023.10262961&partnerID=40&md5=fb0c26950ae77605c354ecf080a9f81d</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/InC457730.2023.10262961" target="_blank" >10.1109/InC457730.2023.10262961</a>
Alternative languages
Result language
angličtina
Original language name
Twitter Sentiment Analysis using Machine Learning Techniques: A Case Study of ChatGPT
Original language description
"ChatGPT is a powerful AI bot developed by OpenAI. This technology has the potential to generate a humanlike response. ChatGPT is a pre-trained system capable of generating chat and understanding human speech. This paper identified the responses of ChatGPT users through related tweets with the help of natural language processing and machine learning techniques. This paper uses textBlob, VADER and human annotation to find the sentiment of each tweet; countvectorizer is used for feature extraction and different machine learning algorithms to classify them into different classes. LeXmo is used to identify the various sentiment analyses, and it is observed that positive and trust emotions are higher than other sentiments. SVM with 10-fold cross-validation shows better results than other techniques. © 2023 IEEE."
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
"Proc. IEEE InC4 - IEEE Int. Conf. Contemp. Comput. Commun."
ISBN
979-835033577-4
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
1-5
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
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Event location
Cham
Event date
Jan 1, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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