SENTIMENT ANALYSIS ON SOCIAL NETWORKING SITES

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SENTIMENT ANALYSIS ON SOCIAL NETWORKING SITES
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CONTENTS

• Abstract
• Introduction
• Existing System
• Proposed System
• Modules
• Conclusion
• References

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ABSTRACT

• Sentiment Analysis on social networking sites is
  a web Application.
• In this user will post his views related to some
  subject or event or product, other users will
  view this post and will comment on this post.
• Comments of various users, based on opinion,
  System will specify whether the posted topic is
  good or bad.
• System will use database and will rank the topic
• The role of the admin is to add post and adds
  keywords in database

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INTRODUCTION

• Sentiment Analysis is the Process of
  computationally identifying and categorizing
  opinions from piece of text, and determine
  whether the writers attitude towards a
  particular topic/product/event is positive or
  negative or neutral.
• Classifying the polarity of a given text as
  positive or negative is the basic task of
  sentiment analysis.
• Sentiment analysis is used in different domains
  such as entertainment, education, shopping etc
• Sentiment analysis is often referred to with
  different names such as Opinion Mining, Sentient
  classification, Sentiment analysis, and Sentiment
  extraction.

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EXISTING SYSTEM

• Information propagates through social networks,
  which is typically supported by the three
  features of microblogs short and simple
  contents.
• More and more users of microblogs tend to share
  small and big deals express opinions and
  sentiments on current issues and discuss various
  topics.
• Therefore, the huge amount of tweets provides us
  with rich information about real world events, in
  which opinions and sentiments are essential.

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DISADVANTAGES

• Problem with calculation of tweets or comments
  score of the tweets or comment the given post.
• Retweeting the comments through the charts and
  telling hot opinions about topic
• Analysing ,calculating the score of tweets.

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PROPOSED SYSTEM

• We design and implement real-time prototype to
  perform opinion mining for tweets.
• Identifies opinion words using syntactic
  relations, and classifies sentiment orientation
  of the sentence with lexicon-based method and
  summarizes all the opinion triples.
• Lexicon-based sentiment analysis algorithm is
  proposed to calculate the sentiment score of
  tweets effectively
• Comments of various users, based on opinion,
  System will specify whether the posted topic is
  good or bad
• Implementation is done using SVM supervised
  machine learning algorithm by creating hyper
  planes

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Advantages

• Automatically give rating to the comments whether
  the given post is Good or Bad.
• To Overcome the calculating score of tweets or
  comments.
• Lexicon-based algorithm is easy to understand.

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Software Requirements

• Front End Python, HTML
• Back End MySql

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Hardware Requirements

• Processor i3
• Hard Disk 5GB
• Memory 1GB RAM

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Modules

• Admin Module
• Add post
• Add Keywords
• User Module
• User signup
• Edit profile
• Comment Module
• Comment
• View comment
• Rating calculation
• Status
• Status Upload

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Conclusion

• This system is useful for the users who need
  review about their new idea and also useful for
  the users who need review about any particular
  event that is posted.
• This application also works as an advertisement
  which makes many people aware about the topic
  posted.

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Reference

• Sentiment analysis and opinion mining,
  synthesis Lectures on Human Language
  Technologies.
• Mining and summarizing customer reviews, in
  proceedings of the Tenth ACM SIGKDD International
  Conference on knowledge Discovery and Data Mining.

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• THANK YOU