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City Transit Rider Tweets: Understanding Sentiments and Politeness

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A2YD9FXQ7" target="_blank" >RIV/00216208:11320/23:2YD9FXQ7 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105202993&doi=10.1080%2f10630732.2021.1903288&partnerID=40&md5=24c2047fe7caf387c42659723074ae96" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105202993&doi=10.1080%2f10630732.2021.1903288&partnerID=40&md5=24c2047fe7caf387c42659723074ae96</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1080/10630732.2021.1903288" target="_blank" >10.1080/10630732.2021.1903288</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    City Transit Rider Tweets: Understanding Sentiments and Politeness

  • Original language description

    "With the expanding popularity of Web 2.0, there has been a huge surge in the use of social media, like Twitter, to express user sentiments or opinions. Delays and breakdowns in transit operations can make riders annoyed and irritated, and as a result, they express their anger and frustration via social media posts. Understanding the tipping points of public frustration will help in developing better solutions. This study aims to develop a framework by developing multilevel sentiment analysis and determine the emotion and politeness measures using transit-related tweets from New York (New York City) and California (San Francisco). The popular hashtags associated with the transit systems of New York and California were collected during 2019. The words associated with negative sentiments widely differ in these two states. Moderate levels of differences are seen in the politeness measures for these two states. Additionally, co-occurrence measures associated with negative emotions identified unique issues based on the demographics. This study demonstrates that Twitter provides a great opportunity to understand the public perception of transit, and the findings can help authorities design a more efficient transit system to improve user experience. © 2021 The Society of Urban Technology."

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    "Journal of Urban Technology"

  • ISSN

    1063-0732

  • e-ISSN

  • Volume of the periodical

    30

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    16

  • Pages from-to

    111-126

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-85105202993