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Volume XVI Issue X

Author Name
Rohit Chaudhary, Harsh Lohiya
Year Of Publication
2024
Volume and Issue
Volume 16 Issue 10
Abstract
This paper explores the application of machine learning (ML) techniques to analyze customer satisfaction from airline-related tweets. Social media platforms like Twitter offer a wealth of real-time customer feedback that can be valuable for airlines to monitor and improve service quality. This research focuses on implementing various machine learning models, including sentiment analysis, emotion detection, and topic modeling, to understand the key factors that influence customer satisfaction in the airline industry. The study also discusses the challenges involved in analyzing unstructured data from tweets and evaluates the effectiveness of different ML approaches for actionable insights.
PaperID
2024/EUSRM/10/2024/61611

Author Name
Vivek Pashine, Shaifali Tripathi
Year Of Publication
2024
Volume and Issue
Volume 16 Issue 10
Abstract
E-commerce is one of the enormous sectors of today era. The adoption of e-commerce growing every day. In today almost 90% of companies have a website or even companies that don’t offer e-commerce services, (Chadwick, 2011).E-commerce is one of the leading sectors. Several kinds of research have done on the impact of e-commerce on consumer behaviour. With the change in technology consumer’s lifestyle, the standard of living, preferences, choice, need and buying habit of consumers also changes. This study is conducted to understand consumers buying behaviour with technology change. This study tried to fill the time gap between existing literature and the current literature. This study will help e-commerce firms to understand the need and wants of consumers, and it also helps to follow current market trends. It aids firms to respond very quickly to change in technology, needs and wants of consumers. This study studied both the positive and negative of consumers because
PaperID
2024/EUSRM/10/2024/61613