Types of Approaches, Applications and Challenges in the Development of
Sentiment Analysis Systems
- URL: http://arxiv.org/abs/2303.11176v1
- Date: Thu, 9 Mar 2023 15:18:34 GMT
- Title: Types of Approaches, Applications and Challenges in the Development of
Sentiment Analysis Systems
- Authors: Kazem Taghandiki, Elnaz Rezaei Ehsan
- Abstract summary: Sentiment analysis is one of the important applications of natural language processing and machine learning.
Millions of comments are recorded daily and it creates a huge volume of unstructured text data.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Today, the web has become a mandatory platform to express users' opinions,
emotions and feelings about various events. Every person using his smartphone
can give his opinion about the purchase of a product, the occurrence of an
accident, the occurrence of a new disease, etc. in blogs and social networks
such as (Twitter, WhatsApp, Telegram and Instagram) register. Therefore,
millions of comments are recorded daily and it creates a huge volume of
unstructured text data that can extract useful knowledge from this type of data
by using natural language processing methods. Sentiment analysis is one of the
important applications of natural language processing and machine learning,
which allows us to analyze the sentiments of comments and other textual
information recorded by web users. Therefore, the analysis of sentiments,
approaches and challenges in this field will be explained in the following.
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