Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/7283
Title: Driving innovation in Crisis Management using Social media apps
Authors: Garg, Abhay
Dhot, Harmeet Singh
Verma, Ruchi [Guided by]
Keywords: Driving innovation
Tweets fetching
Crisis management
Issue Date: 2016
Publisher: Jaypee University of Information Technology, Solan, H.P.
Abstract: Social Media has been active in immense from last decade in assorted domains and obviously it is one of the catalyst for crisis management by the live media. In classical way, the social media is being used for broadcasting, sharing, like and distribution of content to the masses and personal groups. Still, this domain of social media and live tweets is under research. In this project work, a unique application and methodology of integrating Twitter Apps with the programming constructs is implemented so that the fetching, cleaning and prediction of the news and its impact on social community can be analyzed. In this project work, the apps of Twitter are developed using Java for fetch the live tweets so that cumulative prediction and detailed interpretation can be done. Twitter is used in this project as key social media as it is used widely for personal, corporate as well as social applications for assorted variety of devices and platforms. Twitter has mobile apps for iPhone, iPad, Android, Windows 10, Windows Phone, BlackBerry, Firefox OS, and Nokia Series. There are also specialized versions of the website available for the mobile devices, SMS and MMS service. For many years, Twitter has limited the use of third party applications accessing the service by implementing a 100,000 user limit per application. It is one of the excellent cases of social media mining or Twitter mining in specific. In this work, the OAuth is used with Twitter. OAuth is one of the effective and widely used concepts to wrap the code with any programming language. In this work the implementation of twitter mining is done using assorted technologies so that the overall sentiment score can be predicted and analyzed.
URI: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/7283
Appears in Collections:B.Tech. Project Reports

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