Sentiment analysis of 2021 Canadian election tweets

Hao Zhu

doi:10.1117/12.2667211

1 March 2023 Sentiment analysis of 2021 Canadian election tweets

Hao Zhu

Proceedings Volume 12588, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022); 125880C (2023) https://doi.org/10.1117/12.2667211
Event: International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022), 2022, Chongqing, China

Abstract

Sentiment analysis is the technique of automatically evaluating and classifying emotions (often positive, negative, or neutral) from textual data, such as written comments and social media posts. Sentiment analysis is a subfield of natural language processing (NLP) that employs machine learning to classify the emotional tone of textual input. The fundamental model concentrates on positive, negative, and neutral categories, but it can also include the speaker's underlying emotions (pleasure, anger, insult, etc.) and purchase intents. Complexity is added to sentiment analysis by context. For example, consider the exclamation "Nothing!" Depending on whether or not the speaker enjoys the product, the meaning can vary significantly. In order for a machine to comprehend "I like it," it must be able to decipher the context and determine what "it" refers to. In addition, sarcasm and sarcasm can be tricky because the speaker may express a favorable sentiment while intending the opposite.

Citation Download Citation

Hao Zhu "Sentiment analysis of 2021 Canadian election tweets", Proc. SPIE 12588, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022), 125880C (1 March 2023); https://doi.org/10.1117/12.2667211

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