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  A Survey on Opinion Mining on Twitter Data: Tasks, Approaches, Applications and Challenges for Sentimental Analysis  
  Authors : Ch Srinivasa Rao; Dr. G Satyanarayana Prasad; Dr.Vedula Venkateswara Rao
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Social media produces huge amounts of data every minute, which is caused by its conventional implementation over the past years. Modernization in the industry have facilitated new ways of communications between people and created many business prospects. Big Data in social media need efficient and sophisticated processing technologies. Rationale of data mining analyses is to discover valuable patterns and insights from Twitter data. In today’s world, Social Networking websites like twitter, Facebook, tumbler, etc plays a very significant role. Twitter is a micro-blogging which provides tremendous amount of data which can be used for various applications of sentimental analysis like predictions, reviews, elections, marketing etc. Also for a business to execute successfully it is supportive to identify the opinion viewpoints or reviews of the consumers and make amendments in the tactics and services accordingly. Similarly for the consumers it is very valuable to distinguish about the eminence of the products and services in advance. Sentimental Analysis also called opinion mining is a process of extracting information from large amounts of data and classifies them into different classes called sentiments. Opinion mining is a technique of refining the information and revising the emotions associated with a exacting review and consequently discovering the polarity of the review. In this paper, a study on different perception and move towards of Twitter data analysis performed in recent years by means of opinion mining is prepared by taking into consideration the words, retweets, hash tags and emotions.


Published In : IJCSN Journal Volume 7, Issue 1

Date of Publication : February 2018

Pages : 27-35

Figures :04

Tables : 01


Ch Srinivasa Rao : is a Research Scholar in the Department of Computer Science & Engineering at Acharya Nagarnuna University, Guntur, A.P, India. He is working as Associate Professor in SVKP & Dr K S Raju A&Sc College, Penugonda, A.P. He received Masters Degree in Computer Applications from Andhra University and Computer Science Engineering from Jawaharlal Nehru Technological University, Kakinada, India. His research interests include Data Mining, Big Data Analytics.

Dr.G Satyanarayana Prasad : is Professor in the Department of Computer Science Engineering and Dean, Training & Placements at RVR & JC College of Engineering, Chowdavaram, Guntur, India. He received M.S in Computer Science from A&M University, ALABAMA, USA and PhD from Andhra University, Visakhapatnam, India. His research interests include Image Processing, Data Mining, Big Data Analytics. He guided two research scholars for award of their PhD. He published books, several papers in International conferences and journals.

Dr.Vedula Venkateswara Rao : is Professor in the Department of Computer Science Engineering at Srivasavi Engineering College, tadepalligudem, India. He received Matsers Degree in Computer Science Engineering from JawaharLalNehru Technological University Kakinada, Masters Degree In Information Technology from Punjabi University, Patiayala, India and PhD from Gitam University. His research interests include Cloud Computing and Distributed Systems, Data Mining, Big Data Analytics and Image Processing. He published several papers in International conferences and journals.


micro blog, twitter, retweet, hash tag, opinion mining, sentimental analysis, predictions

Opinion miming is an up-and-coming field of data mining to dig out the knowledge from enormous volume of data that may perhaps be customer comments, feedback and reviews on any product or topic etc. Study has been performed to extract opinions in structure of document, sentence and feature level sentiment analysis. It is observed that nowadays opinion mining inclination is touching to the sentimental reviews of twitter data, comments used in Face book on pictures, videos or Face book status. This paper describes a wide-ranging, up-todate assessment on the research work done in various characteristics of sentimental analysis. This paper summarizes some of the most commonly used applications and challenges in sentiment analysis. Now business organizations and academics are putting forward their efforts to find best system for sentiment analysis.


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