{"title":"Web and Social Media Analytics towards Enhancing Urban Transportations: A Case for Bangalore","authors":"Manjira Sinha, P. Varma, Tridib Mukherjee","doi":"10.1145/3068943.3068950","DOIUrl":null,"url":null,"abstract":"Cities today are typically plagued by multiple issues such as âĂŞ traffic jams, garbage, transit overload, public safety, drainage etc. Citizens today tend to discuss these issues in public forums, social media, web blogs, in a widespread manner. Given that issues related to public transportation are most actively reported across web-based sources, we present a holistic framework for collection, categorization, aggregation and visualization of urban public transportation issues. The primary challenges in deriving useful insights from web-based sources, stem from: (a) the number of reports; (b) incomplete or implicit spatio-temporal context; and the (c) unstructured nature of text in these reports. This paper provides the text categorization techniques that can be adopted to address specifically these challenges. The work initiates with the formal complaint data from the largest public transportation agency in Bangalore, complemented by complaint reports from web-based and social media sources. An easy to navigate and well-organized dashboard is developed for efficient visualization. The dashboard is currently being piloted with the largest transportation agency in Bangalore.","PeriodicalId":345682,"journal":{"name":"Proceedings of the 2nd International Workshop on Network Data Analytics","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Workshop on Network Data Analytics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3068943.3068950","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Cities today are typically plagued by multiple issues such as âĂŞ traffic jams, garbage, transit overload, public safety, drainage etc. Citizens today tend to discuss these issues in public forums, social media, web blogs, in a widespread manner. Given that issues related to public transportation are most actively reported across web-based sources, we present a holistic framework for collection, categorization, aggregation and visualization of urban public transportation issues. The primary challenges in deriving useful insights from web-based sources, stem from: (a) the number of reports; (b) incomplete or implicit spatio-temporal context; and the (c) unstructured nature of text in these reports. This paper provides the text categorization techniques that can be adopted to address specifically these challenges. The work initiates with the formal complaint data from the largest public transportation agency in Bangalore, complemented by complaint reports from web-based and social media sources. An easy to navigate and well-organized dashboard is developed for efficient visualization. The dashboard is currently being piloted with the largest transportation agency in Bangalore.