Design and Analyze the Machine Learning Based Sarcasm Prediction Model for Social Media Context

Autor: B. Rajani, Sameer Saxena, B. Suresh Kumar

Publikováno v: International Journal of Intelligent Systems and Applications in Engineering; Vol. 11 No. 5s (2023): Special Issue on Applications of Advanced Engineering Technologies; 156-163

Sentiment Analysis examines the predominance of sarcastic language and its difficulties detecting sentiment in the text. The identification of sarcasm in the text is the focus of automatic sarcasm detection. Sarcasm recognition has been more popular

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=issn21476799::7ab1848bda0cf0bd3359204523c9bba4
https://www.ijisae.org/index.php/IJISAE/article/view/2762

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Statistical Properties of a New Social Media Context Awareness Scale (SMCA)—A Preliminary Investigation

Autor: Ramona Lile, Dana Rad, Tiberiu Dughi, Gavril Rad, Edgar Demeter, Valentina Emilia Balas

Publikováno v: Sustainability, Vol 12, Iss 5201, p 5201 (2020)
Sustainability
Volume 12
Issue 12

In the Internet of Things era, or in the digitalization and mediatization of everything paradigm, where context awareness computing is on the rise, people are also facing a new challenge, that of being aware of the digital contexts, in all situations

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::258a7e13f1b9561c54b3ec223e1fb013
https://www.mdpi.com/2071-1050/12/12/5201

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