Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (8): 1139-1150.doi: 10.23940/ijpe.20.08.p1.11391150

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Potential Extensions and Updates in Social Media for Twitter Developers

Ankit Kumar, Dipansha Chhabra, Bhavya Mendiratta, and Adwitiya Sinha*   

  1. Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, Sector-62, Uttar Pradesh, India
  • Submitted on ; Revised on ; Accepted on
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  • About author:Ankit Kumar is currently pursuing a B.Tech. from Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India. His research interests include social networking and graph analysis.Dipansha Chhabra is currently pursuing a B.Tech. from Jaypee Institute of Information Technology. Her research interests include Twitter science and data mining.Bhavya Mendiratta is currently pursuing a B.Tech. from Jaypee Institute of Information Technology. His research interests include social networking, social media analysis, text mining, data mining, and data science.Adwitiya Sinha received her Ph.D. from Jawaharlal Nehru University (JNU), New Delhi, India in 2015. She received her master's degree in computer science and technology in 2010 from JNU. She was awarded First Rank certificate in M.Tech. in 2008. She received a senior research fellowship (SRF) from the Council of Scientific & Industrial Research (CSIR), New Delhi, and was also awarded a research scholarship from the University Grants Commission (UGC) for her research in wireless sensor networks. Presently, she is working as an assistant professor at Jaypee Institute of Information Technology. She is a senior member of IEEE. Her research areas mainly include performance analysis of wireless sensor networks, complex networks, data science, and large-scale graphs analytics.

Abstract: With the increase in the impact of social networking in our daily lives, the world around us has become more transparent and dynamic. Our research is focused on bringing such technological benefits to social media users in the form of useful updates. These updates will make online users aware of sentiments in community gossip, the spread of global media trends, and responses to their posts on social media. For this purpose, we have conducted a case study over a social media trend on Twitter and proposed a set of analytical metrics that can assist Twitter developers in making their social platform more informative and interactive. Though presently Twitter offers certain basic parameters through API calls, the user interface lacks insightful statistics for the benefits of the end-users. Our case study is conducted in two phases, involving basic and advanced social network analysis. The basic research includes finding users who triggered the online trend, featuring the popularity of the trend, acquiring the location of users who mentioned the hashtag, and detecting the devices that have been used frequently to tweet on the trend. We proposed to the developers advanced solutions with more insightful analytics, which involves the identification of users whose content received maximum reach and reveals influential users’ popularity amongst others tweeting with the same hashtag. Furthermore, the actual and potential reach of online social trends is computed along with sentiment analysis. Our work also suggests the availability of an ego-centric network of the most influential user in the trend for visualizing real-time diffusion of its reach.

Key words: developer social network, Twitter developer, social media, trend outreach, geospatial reach, ego-centric network, network diffusion