Apurva Pathak, Bidyut Kr. Patra, Arnab Chakraborty, Abhishek Agarwal
{"title":"A City Traffic Dashboard using Social Network Data","authors":"Apurva Pathak, Bidyut Kr. Patra, Arnab Chakraborty, Abhishek Agarwal","doi":"10.1145/2778865.2778873","DOIUrl":null,"url":null,"abstract":"With the growing urbanization and globalization, long commute and traffic problems have become the everyday nightmare of an Indian metro city dweller. The non-existence of a singular dashboard, which can provide holistic view of the city traffic, has aggravated this problem manifold for the traffic authorities and its citizens. This paper describes the methodology we employed for CoDS 2015 Data Challenge to solve this problem. We show how data from social network can derive useful information about the road and traffic issues in a city. We propose to design a dashboard for obtaining real-time view of the traffic data scattered across various user status updates, tweets and comments on social networks using state-of-the-art machine learning algorithms. We present empirical results and discuss various methods for extracting useful information from the social feeds. Proposed dashboard can provide a straight actionable information to the users and traffic authorities for handling traffic issues in efficient manner.","PeriodicalId":116839,"journal":{"name":"Proceedings of the 2nd IKDD Conference on Data Sciences","volume":"166 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd IKDD Conference on Data Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2778865.2778873","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
With the growing urbanization and globalization, long commute and traffic problems have become the everyday nightmare of an Indian metro city dweller. The non-existence of a singular dashboard, which can provide holistic view of the city traffic, has aggravated this problem manifold for the traffic authorities and its citizens. This paper describes the methodology we employed for CoDS 2015 Data Challenge to solve this problem. We show how data from social network can derive useful information about the road and traffic issues in a city. We propose to design a dashboard for obtaining real-time view of the traffic data scattered across various user status updates, tweets and comments on social networks using state-of-the-art machine learning algorithms. We present empirical results and discuss various methods for extracting useful information from the social feeds. Proposed dashboard can provide a straight actionable information to the users and traffic authorities for handling traffic issues in efficient manner.