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Sentiment analyzer and opinion mining

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In recent times, research activities in the areas of Opinion and Sentiment analysis in natural language texts and other media are gaining ground under the umbrella of subjectivity analysis. The reason may be the huge amount of available text data in the Social Web in the forms of news, reviews, blogs, chats and even twitter. Though Sentiment analysis from natural lan-guage text is a multifaceted and multidisciplinary problem, in general, the term “sentiment” is used in reference to the automatic analysis of evaluative text.

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Sentiment analyzer and opinion mining

  1. 1. SENTIMENT ANALYZER AND OPINION MINING ON TWITTER DATA STREAM Name of supervisor -Ms. Akanksha Bhardwaj Name of Student -Saumya Chaturvedi ( 9910103430) MAJOR PROJECT On
  2. 2. Agenda..  Objective  Working  Modules in the Project wrt Design  Control Flow Diagram  Sequence Design  Software requirements  Future Scope  Conclusion
  3. 3. Objective  Stream twitter data on a particular topic on real time basis  Checking for semantic orientation of this data efficiently using supervised learning approach.
  4. 4. Modules in the Project wrt Design  PYTHON PROGRAMMING LANGUAGE TOOLS  Python programming language was chosen because the existing systems are programmed in Python, therefore using the same language is natural. The availability of modules that helped in the development process contributed to choosing the language. Python offers good portability across different environments. The tools used include NeuroLab library which provides pre-existing neural network algorithms implemented in Python, and Natural Language Toolkit that was used for Part-of- Speech tagging
  5. 5.  Natural Language Toolkit Natural Language Toolkit (NTLK) is an open source library, distributed under Apache 2.0 license, multiplatform collection of tools and modules for natural language processing and text analysis, available in Python programming language. It provides a large set of tools and algorithms for text tokenization, stemming, tagging, chunking, parsing, classification, clustering, measurements and semantic interpretation. It also provides an access to many text corpora and lexicon. In this work, NLTK is used part-of-speech tagging from documents.
  6. 6.  Tweepy  Tweepy is one of python’s open source libraries which play an important role in this project. It is used to stream twitter data stream on a real time basis. It is hosted on GitHub and enables Python to communicate with Twitter platform and use its API
  7. 7. Control flow diagram
  8. 8. Requirements  Software Interface:  Python(Version Number: 2.7)  Tweepy  NLTK Library
  9. 9. Future Scope  Our review-oriented website would serve as an efficient tool for media analysis on various products.  This idea can also be extended in a way to serve as an effective review-summarizer that would not only produce the poll result of the reviews but would, also summarize the text of various review in simple words for the user.
  10. 10. Conclusion  This project can directly affect the industry’s time and performance, in terms of the customer relationship.  It is possible to know what user wants to express by their reviews. That is what is the concept of – “Sentiment Analyzer”.

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