PPT FOR BIG

SEMINAR REPORT ONMINING BIGDATA: CURRENT STATUS, AND FORECAST TO THE FUTURE USING TWITTER ANALYZER

PRESENTED BY: C.VENKATESH PRASAD(113G1A0551)

N.RUPA(113G1A0539)A.THARUN(113G1A0549)L.SUDEEP REDDY(113G1A0546)VI-CSE(B.TECH)KMMITS

UNDER THE GUIDANCE OF:Mrs. PUSHPA KUMARI, M.Tech

CONTENTS1. INTRODUCTION2. SYSTEM REQIREMENTS3. SYSTEM DESIGN4. MODULES5. FUTURE ENHANCEMENT6. CONCLUSION7. BIBLIOGRAPHY

1.INTRODUCTION

The data gathering from Twitter is example of Bigdata collection. Analysis of Bigdata is a challenging task, and is difficult with normal data mining tools.

A new way of analysis is needed and it is the aim of our present work.

DRAWBACKS OF EXISTING SYSTEM:• Highly Time consuming• Not efficient with current data mining tools.

PROPOSED SYSTEM:

• The added feature or modification in proposed system to existing one is ,the future businesses can use this data to determine whether or not their current social media strategy is working by reviewing if their Tweets are resonating with their Twitter audience. This information can be used to quickly change initiatives that aren’t working or can be used to plan out future content strategies.

ADVENTAGES OF PROPOSED SYSTEM:

• parallel massive graph analysis.• More efficient.• High ratio of memory requests to computation can

be tolerated via multithreading.

2.SYSTEM REQUIREMENTS

Software requirements:• Operating System : Windows• Technology : Java and J2EE• Web Technologies : Html, JavaScript, CSS• IDE : Eclipse• Web Server : IBM Bluemix• Database : CloudantNoSQL• Java Version : J2SDK1.7

Hardware requirements:Hardware : PentiumRAM : 1GB

3.SYSTEM DESIGN

4.MODULESFirst we can create project name.

CREATE AN APPLICATION FOR ANALYZER:

Here we can create the analyzer for an analyzing project data.

ANALYZER CONNECT TO THE TOOL:

Our analyzer is connect to the Bluemix tool.

EDIT APPLICATON ENVIRONMENT VARIABLES:

Accessing data using twitter authentication keys.

APLICATION CONNECT TO CloudantNoSQL DB:

After connection establishment the tool provide serve like services delivered through CloudantNoSQL.

INFLUENCE ANALYZER:

INFLUENCE RESULT:

INFLUENCE LIST:

5.FUTURE ENHANCEMENT

• While doing this work we focus on the problem of predicting box office revenues of movies for the sake of having a clear metric of comparison with other methods, This method can be extended to a large panoply of topics, ranging from the future rating of products to agenda setting and election outcomes.

6.CONCLUSION

• We expect our study can contribute both to theory and to practice. Interesting, postings from users with many followers have a greater impact on same-day returns, while postings from users with few followers have a greater impact on future returns.

7.BIBLOGRAPHY

• [1] Algesheimer, R., Dholakia, U., and Hermann, A., "Interplay between Brand and Brand Community: Evidence from European Car Clubs", Available at SSRN 534542, 69(3), 2004, pp. 19-34.

• [2] Andersen, P.H., "Relationship Marketing and Brand Involvement of Professionals through Web-Enhanced Brand Communities: The Case of Coloplast", Industrial Marketing Management, 34(1), 2005, pp. 39-51.

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