An overview of Sentiment Analysis for Web-based Big Data

۱*۱ [e-mail] today's digital era, consumers increasingly turn to the internet to seek feedback on a wide array of products and services. However, the sheer volume of data available online presents a significant challenge for applications to effectively manage and utilize this information. Compounding this challenge is the fact that data comes in various formats and is constantly evolving. Hence, there is a pressing need for robust systems capable of analysing and categorizing web reviews on a large scale—a task commonly referred to as opinion mining or sentiment analysis. Sentiment analysis, at its core, involves deciphering the attitudes and opinions expressed in textual data, making it a complex yet promising field. By leveraging techniques from information retrieval and computational linguistics, sentiment analysis endeavours to extract meaningful insights from the vast sea of online reviews. This paper delves into the intricacies of sentiment analysis, shedding light on the process and highlighting the role of machine learning techniques in sentiment classification. Additionally, it explores the future challenges awaiting researchers and practitioners in the realm of opinion mining for big data.Keywords:

کلیدواژه ها:

Web Mining ، Opinion Mining ، Sentiment Classification ، Text Classification ، Big Data Analysis