Using Social Networking APIs to Collect Real-time Data for Analytics

Weidong Liao, Robert Chhoeut

Abstract


Social Media platforms have been widespread since the advent of web 2.0, ever since, users have been contributing content in the form of various media such as text messages, pictures, video, blog posts and other formats. The scale of data amassed from these contributions offer opportunities for data mining and analytics which in turn may offer meaningful interpretations.

   Currently various tools exist for fetching and analyzing social media data. The purpose of this project is to uncover methods for fetching real-time data among various social networking platforms for analytical use. APIs (Application programming interfaces) exist for simplifying an implementation of an application’s functionality.

   Using APIs such as Twitter4j, Restfb, and Google+ API, a Java test application was written to utilize API search features in to retrieve various queries of data. The result was a test application which retrieved and outputted data into a file. However the drawbacks were API authentication requirements, data fetching rate limit restrictions, and deprecated/removed features. In general APIs offer a solution in fetching data and building applications, but may include restrictions for the public’s access depending on Social Media platform.


Keywords


Social Media, API, Data Analytics

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