Deciphering Public Sentiment on iPhone 14: A BERT-Based Analysis of Twitter Discourse

Abstract

The study delves into understanding the sentiment of Twitter users towards the iPhone 14 by employing sentiment analysis models. Recognizing the limitations of traditional sentiment analysis tools, the research utilizes the BERT model, known for its bidirectional understanding of textual context. Initially, the study observed a prevailing negative sentiment using general models. However, after refining the approach using BERT, a more balanced representation of sentiments was observed. The BERT model's results highlighted both positive and negative reactions towards the iPhone 14 on Twitter, with distinct peaks in sentiment scores. The research underscores the importance of leveraging advanced models like BERT for tasks requiring nuanced understanding, providing stakeholders in the technology domain with comprehensive insights into public sentiment.