In the current information age, a wide variety of social media platforms and news sites have been developed and become an important part of modern life. It also provides vast amounts of user-generated data obtained from various social networking and news platforms that provide new insights to businesses and governments. However, it has become difficult to extract useful information from the vast amount of information effectively. Sentiment analysis and topic classification provides an automated way to analyze emotions, emotion, and opinion to address this problem. In the existing literature, a large number of scientists have worked to improve the performance of different emotion works or apply them to different fields using data from social networking and news platforms. This paper explores the methods and approaches of sentiment analysis and classification of topics, techniques, challenges and problems faced by scientists in the study of sentiment analysis. It gives a comprehensive overview of the objectives and applications of sentiment analysis, and the ways in which they are used in different fields of application. It also touches on some of the different studies and highlights challenges related to data sets, text languages, methods of analysis and eva‎luation measures. This paper contributes to research on sentiment analysis and topic classification and can help researchers analyze sentiment in their future studies.

7/6/2024 12:00:00 AM

83193

1403/04/25

Sentiment Analysis and Topics Classification in Social Media and News Sites

تجزيه و تحليل احساسات، طبقه بندي موضوعات، رسانه هاي اجتماعي، تكنيك هاي تجزيه و تحليل داده ها، مجموعه داده ها

Sentiment Analysis, Topic Classification, Social Media, Data Analysis Techniques, Data Sets