Weighted Trilateration Using Domain Knowledge for Event Localization in Twitter Data

Authors

DOI:

https://doi.org/10.59297/6av2vm85

Keywords:

social networking, event localization, weighted trilateration

Abstract

In this paper, we develop a novel approach called Domain Adapted Weighted Trilateration (DAWT). We use the idea of there are reference coordinates at known locations that scrape the microblog (tweet) counts in time and space (circular regions around the reference coordinate). The change in counts of tweets would be indicative of an event pattern. We propose the use of DAWT to combine the information from multiple reference points to find the exact location of the event. We propse the use of domain knowledge in the form of counts of tweet or spatial relationship between reference points to calculate the weights for trilateration. We use microblogging data collected from Twitter to evaluate our model and compare it with other baseline methods.

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Author Biographies

  • Usman Anjum, University of Cincinnati

    Usman Anjum is a Research Associate in the Department of Computer Science at the University of Cincinnati. Previously, he worked as a Research Associate at the University of Arkansas, Fayetteville. He holds a PhD in Information Science from the University of Pittsburgh and a Master's in Telecommunications from the University of Maryland. He has collaborated on research projects with the Cincinnati Children's Hospital Medical Center (CCHMC), Google, and Deloitte. Additionally, he is a recipient of the prestigious Fulbright Scholarship. He has bachelor's degree in Electronics Engineering and also has work experience in Siemens and  Rohde & Schwarz.

  • Justin Zhan, University of Cincinnati

    Justin Zhan is the Head of Department of Computer Science, College of Engineering and Applied Science, University of Cincinnati. His research interests include data science, artificial intelligence, blockchain technologies, biomedical informatics, information assurance, and social computing. He was a steering chair of the IEEE International Conference on Social Computing (SocialCom), IEEE International Conference on Privacy, Security, Risk and Trust (PASSAT), and IEEE International Conference on BioMedical Computing (BioMedCom). He has been an editor-in-chief of the International Journal of Privacy, Security and Integrity, and International Journal of Social Computing and Cyber-Physical Systems. He has served as a conference general chair, a program chair, a publicity chair, a workshop chair, and a program committee member for 150 international conferences; he has also served as an editor-in-chief, editor, associate editor, guest editor, editorial advisory board member, and editorial board member for 30 journals. He has published 250 articles in peer-reviewed journals and conferences and delivered more than 30 keynote speeches and invited talks. He has been involved in more than 60 projects as a principal investigator (PI) or a Co-PI, which were funded by the National Science Foundation, Department of Defense, National Institute of Health, etc.

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Published

2025-05-06

Conference Proceedings Volume

2025: 22nd International ISCRAM Conference, Halifax, Canada: Managing and Responding to Coastal Disasters and Climate Change

Section

ISCRAM Proceedings

How to Cite

Anjum, U., & Zhan, J. (2025). Weighted Trilateration Using Domain Knowledge for Event Localization in Twitter Data. Proceedings of the International ISCRAM Conference. https://doi.org/10.59297/6av2vm85

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