What to Track on the Twitter Streaming API? A Knapsack Bandits Approach to Dynamically Update the Search Terms
By Kumar Sumeet, Kathleen Carley
ASONAM Conference, Vancouver, Canada | 2019
Citation
Sumeet, Kumar., Carley, Kathleen. What to Track on the Twitter Streaming API? A Knapsack Bandits Approach to Dynamically Update the Search Terms ASONAM Conference, Vancouver, Canada .
Copyright
ASONAM Conference, Vancouver, Canada, 2019
Share:
Abstract
We use Twitter streaming API for many purposes like monitoring brands and discovering events. Because Twitter Streaming API only allows tracking words (commonly called'search-terms'), the data collection goal needs to be formulated in terms of search terms. Twitter limits the number of search terms that can be tracked using the API, and the number of tweets retrieved per search-term depends on the terms being tracked. Therefore it's crucial to use a small set of highly relevant terms for tracking.

Sumeet Kumar is an Assistant Professor of Information Systems at the Indian School of Business (ISB). He studies problems at the intersection of technology and society. He is interested in analysing user behaviour, quantifying polarisation on online forums , and finding advertisements disguised as regular content on online platforms. His current focus is on identifying implicit or hidden advertisements in videos posted on children’s platforms such as YouTube Kids.

Additionally, Professor Kumar has conducted research in software design and development, with particular emphasis on user experience. He has investigated the use of mobile phone sensors during emergencies to improve situational awareness. His study on the Wireless Emergency Alerts (WEA) service in the United States addressed several issues of critical importance to emergency alerts effectiveness and adoption. Notably, some of his research recommendations was included in the US Federal Communications Commission (FCC) proposed changes to WEA.

He completed his undergraduate education at Indian Institute of Technology (IIT) Kanpur. He holds two Master’s degrees—in Software Engineering and in Machine Learning--both from Carnegie Mellon University, where he also earned his doctorate degree.

Sumeet Kumar
Sumeet Kumar