Exploration of road traffic tweets for congestion monitoring

Lim Cheng Yang, Bhawani Selvaretnam, Poo Kuan Hoong, Ian K.T. Tan, Ewe Kok Howg, Lau Heng Kar

Research output: Contribution to journalArticleResearchpeer-review

6 Citations (Scopus)

Abstract

Online social network services such as Twitter and Facebook have gained popularity in recent years with continuous increase of users. This is especially true for Twitter, a popular micro-blogging service that enables users to send tweets which contain valuable data in real-time. Real-time tweets information can be used in many areas and one of the least explored areas is crowdsourcing of road traffic conditions. We have found that not many people tweet about traffic conditions; however, there are formal sources that keep their accounts updated with the latest traffic info. In this paper, we present an analysis of tweets that are related to the traffic conditions in Malaysia. Detailed analysis was conducted to understand the structures and the nature of the traffic tweets. Based on our analysis, we found that the real-time nature of the tweets is useful in reporting road traffic conditions and such information will be useful to the road-users.

Original languageEnglish
Pages (from-to)141-145
Number of pages5
JournalJournal of Telecommunication, Electronic and Computer Engineering
Volume8
Issue number2
Publication statusPublished - 2016
Externally publishedYes

Keywords

  • Data mining
  • Natural language processing
  • Road traffic
  • Twitter

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