Work with Streaming Data using Twitter API to Build a Job Portal
Jayakumar Sadhasivam1, Senthil Jayavel2, Arpit Rathore3, Akshay Pratap Singh4, Avi Singh5, J Cynthia6
1Jayakumar Sadhasivam, School of Information Technology and Engineering (SITE), Vellore Institute of Technology, Vellore (Tamil Nadu), India.
2Senthil Jayavel, Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
3Arpit Rathore, School of Information Technology and Engineering (SITE), Vellore Institute of Technology, Vellore (Tamil Nadu), India.
4Akshay Pratap Singh, School of Information Technology and Engineering (SITE), Vellore Institute of Technology, Vellore (Tamil Nadu), India.
5Avi Singh, School of Information Technology and Engineering (SITE), Vellore Institute of Technology, Vellore (Tamil Nadu), India.
6J Cynthia, Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 19 August 2019 | Revised Manuscript received on 10 September 2019 | Manuscript Published on 17 September 2019 | PP: 1039-1042 | Volume-8 Issue-2S8 August 2019 | Retrieval Number: B10090882S819/2019©BEIESP | DOI: 10.35940/ijrte.B1009.0882S819
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this digital era that we are living in everyone is obsessed with mobiles, computers and is on the internet, so job portals play an important role in aiding job seekers in their job hunt. It will make them aware of the various job openings, and they will not miss an opportunity. The job is essential for the students who do their graduation, post-graduation, etc. So, we know that there are lots of websites where can we can find the lots of vacancy in various firms but the website is not updated the job vacancy minutely or many of them not updated the job vacancy hourly so we cannot get the minutely updated about the jobs. The vacancy appears quickly on social networking websites like Twitter, LinkedIn, Facebook, etc. as compared to appears on the job websites like indeed.com, monster.com, etc. so many of the people are not on these social media or maybe not regular on the social media, so there is a chance miss the opportunity. Our objective with this paper is to come up with a portal that will provide the user’s details about various job openings in respective domains. The portal will stream data from Twitter API to find out the recently published jobs. Classification of relevant and irrelevant tweets is accomplished using the machine-learning algorithm, i.e., Logistic Regression. Using the algorithm, we have measured the 97% accuracy.
Keywords: Twitter, API, Job Portal, Stream Data, Machine-Learning, Logistic Regression.
Scope of the Article: Data Mining and Warehousing