Location

London

Event Website

http://www.csce2016.ca/

Description

Public involvement in operation and planning of transit services is becoming a major focus of public transportation agencies. With the growing population and diversification of ideas, distilling knowledge from public opinion to incorporate into decision support systems is a major challenge for transit agencies. The common practice is to collect information from customers via Customer Satisfaction Surveys (CSat). Although such surveys provide useful insight for transit agencies, their design, data collection, and interpretation is expensive and time consuming. Because of the qualitative nature of the questions in these surveys, inconsistency in respondents’ perception of the survey questions is another challenge. Furthermore, for management and decision-making purposes, the results of surveys should be quantified into various key performance indicators. Lack of a standard quantification system causes some biases in the reported results. The advent of online social media has introduced a new bidirectional communication system. Developing a linguistic-based system to interpret customer discussions in social media about the transit system and to transform the discussions into useful information for the agency could overcome some deficiencies existing in CSat. The current study develops a standard lexical resource to categorize online discussions on Twitter into different Level of Service (LOS) indicators.


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Jun 1st, 12:00 AM Jun 4th, 12:00 AM

TRA-929: A STANDARD LEXICON TO MEASURE THE LEVEL OF SERVICE OF PUBLIC TRANSPORTATION SERVICES THROUGH ONLINE TRANSIT-ORIENTED DISCUSSIONS

London

Public involvement in operation and planning of transit services is becoming a major focus of public transportation agencies. With the growing population and diversification of ideas, distilling knowledge from public opinion to incorporate into decision support systems is a major challenge for transit agencies. The common practice is to collect information from customers via Customer Satisfaction Surveys (CSat). Although such surveys provide useful insight for transit agencies, their design, data collection, and interpretation is expensive and time consuming. Because of the qualitative nature of the questions in these surveys, inconsistency in respondents’ perception of the survey questions is another challenge. Furthermore, for management and decision-making purposes, the results of surveys should be quantified into various key performance indicators. Lack of a standard quantification system causes some biases in the reported results. The advent of online social media has introduced a new bidirectional communication system. Developing a linguistic-based system to interpret customer discussions in social media about the transit system and to transform the discussions into useful information for the agency could overcome some deficiencies existing in CSat. The current study develops a standard lexical resource to categorize online discussions on Twitter into different Level of Service (LOS) indicators.

http://ir.lib.uwo.ca/csce2016/London/Transportation/11