INTRODUCTION CHAPTER 1 1.1PROJECT

2000 WordsApr 23, 20198 Pages
INTRODUCTION CHAPTER 1 1.1PROJECT SUMMARY:  Unstructured data on opinions, emotions, and attitudes contained in sources like social media, blogs, online product reviews and customer support interactions is called the sentiment data.  An enterprise may analyze sentiment about products, services, competitors and reputation. In twitter people post real time messages about their opinions on a variety of topics and express sentiments for products they use in daily life.  Each tweet is 140 character in length.Twitter generates around 250 million tweets daily.  It is a challenge to gather all such relevant data, detect and summarize the overall sentiment on a topic.  For this purpose, all the…show more content…
Starting from being a document level classi-fication task, it has been handled at the sentence level and more recently at the phrase level. Microblog data like Twitter, on which users post real time reactions to and opinions about “every- thing”, poses newer and different challenges. The platform used for this system is the R language. Features of R:  It is easier to create graphics and animations.  R is capable of working with big-data. Matrix manipulation and sorting becomes easier.  It is open source.  R is an interactive programming language.  Statistical analytics becomes easier with R. SYSTEM ANALYSIS CHAPTER 2 2.1 STUDY OF EXISTING SYSTEM:  Currently, there are many offline software for analysis wherein we need to provide the data to be analyzed  The user needs to manually get the data related to specific hash tags from twitter. It is a cumbersome process.  The accuracy of the sentiment analysis done on such analytics software is about 30-40% as these software are not dedicated for analysis of microblogs. 2.2 PROBLEM WITH EXISTING SYSTEM:  Data is to be gathered manually.  It is time consuming.  Format of the gathered data must be converted as required by the software. 2.3 REQUIREMENT OF NEW SYSTEM:  The task of retrieving the tweets can be made automatic  The task of formatting the tweets can be reduced  The accuracy
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