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Sentiment Analysis on social networking sites

Sentiment Analysis is the Process of computationally identifying and categorizing opinions from piece of text, and determine whether the writeru2019s attitude towards a particular topic/product/event is positive or negative or neutral.<br>

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Sentiment Analysis on social networking sites

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  1. SENTIMENT ANALYSIS ON SOCIAL NETWORKING SITES

  2. CONTENTS: Abstract ► Introduction ► Existing System ► Proposed System ► Modules ► Conclusion ► References ►

  3. 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 ►

  4. INTRODUCTION: Sentiment Analysis is the Process of computationally identifying and categorizing opinions from piece of text, and determine whether the writer’s 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. ►

  5. 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. ►

  6. 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. ▪

  7. 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 ►

  8. 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. ►

  9. Software Requirements: Front End : Python, HTML ► Back End : MySql ►

  10. Hardware Requirements: Processor : i3 ► Hard Disk : 5GB ► Memory : 1GB RAM ►

  11. Modules: ? ? Admin Module: ▪ Add post ▪ Add Keywords ?User Module: ▪ User signup ▪ Edit profile ? ? Comment Module: ▪ Comment ▪ View comment ▪ Rating calculation ?Status: ▪ Status Upload

  12. 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. ►

  13. 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. ►

  14. About TechieYan Technologies: TechieYan Technologies offers a special platform where you can study all the most cutting-edge technologies directly from industry professionals and get certifications. TechieYan collaborates closely with engineering schools, engineering students, academic institutions, the Indian Army, and businesses. Address: 16-11-16/V/24, Sri Ram Sadan, Moosarambagh, Hyderabad, Telangana 500036 Phone no: 070755 75787 Website : https://techieyantechnologies.com/

  15. THANK YOU

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