A Survey of Real-Time Social-Based Traffic Detection

July 07, 2020 ยท The Cartographer ยท ๐Ÿ› Intelligence and Security Informatics

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: A Survey of Real-Time Social-Based Traffic Detection"

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Authors Hashim Abu-gellban arXiv ID 2007.04100 Category cs.SI: Social & Info Networks Cross-listed cs.LG Citations 3 Venue Intelligence and Security Informatics Last Checked 4 days ago
Abstract
Online traffic news web sites do not always announce traffic events in areas in real-time. There is a capability to employ text mining and machine learning techniques on the twitter stream to perform event detection, in order to develop a real-time traffic detection system. In this present survey paper, we will deliberate the current state-of-art techniques in detecting traffic events in real-time focusing on five papers [1, 2, 3, 4, 5]. Lastly, applying text mining techniques and SVM classifiers in paper [2] gave the best results (i.e. 95.75% accuracy and 95.8% F1-score).
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