Extraction and Analytics from Twitter Social Media with Pragmatic Evaluation of MySQL Database
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2018 by IJCTT Journal|
|Year of Publication : 2018|
|Authors : Abhijit Bandyopadhyay|
|DOI : 10.14445/22312803/IJCTT-V57P114|
Abhijit Bandyopadhyay,"Extraction and Analytics from Twitter Social Media with Pragmatic Evaluation of MySQL Database". International Journal of Computer Trends and Technology (IJCTT) V57(2):74-79, March 2018. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
With the escalating use of web based platforms and technology loaded devices, a number of online communication environments are used. Social Media is one of the prominent as well as effective modes of communication for personal or group based broadcasting of emotions or sentiments. The process of communication and data transmission to like-minded or friends is traditionally known as social media in which a strong and performance aware web based environment is used as a media to deliver and transmit the emotions. The process of extracting and mining the data flowing on such channels is traditionally known as sentiment mining. This process is done using web based APIs which communicate with the live servers of social media. Now, the key point arises on the efficiency of database engine because the real time streaming data is very complex for a classical relational database management system. This research work focus on the implementation of Twitter Social Media Extraction and Sentiment Mining with the performance evaluation of MySQL Database System on multiple parameters. Twitter is one of the leading and prominent social media platforms that is used for the distribution, dissemination and broadcasting of views in multiple formats. A number of celebrities, political speakers, leaders and key personalities are using Twitter so that their views and sentiments can be transferred to the whole world. Even the media groups and news channels are using Twitter for the distribution of news in form of tweets to all the devices and handhelds. In this research manuscript, an effectual approach for the mining of social media tweets is presented to be used so that the understandable as well as prediction based popularity extraction can be implemented. The present work is based on the matching of positive and negative words from social media tweets which are proposed to be stored in a database engine so that the overall performance of database system with the real time data can be evaluated. The implementation aspects in this work shall use MySQL as back-end database in which the live tweets from Twitter Server based on a Java based platform. Any keyword can be searched on the Java based application that will communicate with Twitter Servers and the live streaming tweets shall be inserted in the MySQL Table. Using specific applications, plugins and programming interfaces, the information regarding particular keyword can be fetched and then the processing to be done from MySQL. The dynamic insertion of records in terms of real time streaming data from Twitter is projected to be done on different attributes of database including User Timeline, Tweets / Retweet, Number of Followers, Platform and Devices Used, Timestamp and Retweet Status, Friends’ List, List of Retweets and Related Timezone, Retweet Platform and Followers, Individual Followers’ Tree and many others. The key focus in this research work is to evaluate the efficiency factor associated with MySQL in handling the real time data from Twitter Servers based on the dynamic keywords to be processed in the Java based application.
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Twitter Database Interaction, Twitter Database Channels, Sentiment Extraction, Social Media Mining, Text Mining, Twitter Mining