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Sentiment Analysis of National Tourism Organizations on Social Media

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F20%3A50016698" target="_blank" >RIV/62690094:18450/20:50016698 - isvavai.cz</a>

  • Result on the web

    <a href="http://eldok.svkhk.cz/out/Hradec_Economic_Days/Hradec_Economic_Days_2020/Hradec_Economic_Days_2020.pdf" target="_blank" >http://eldok.svkhk.cz/out/Hradec_Economic_Days/Hradec_Economic_Days_2020/Hradec_Economic_Days_2020.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Sentiment Analysis of National Tourism Organizations on Social Media

  • Original language description

    Social media is probably currently the largest source of human-generated text content. User opinions, feedback, comments, and criticism points to their mood and sentiment towards different topics, especially destinations, products or services. The rapid rise in amount of data and constantly generated content require the need to automate both data acquisition and processing to identify important information and knowledge. Sentiment analysis provides the opportunity to detect opinion, feeling and sentiment from unstructured texts on social media. To analyze the sentiment Machine Learning with Google Natural Language API Client Libraries and Google Cloud SDK (Software development kit) was used. NTOs (National Tourism Organizations) social media have been chosen for analysis in which emotional messages can be expected to stimulate potential visitors to the destination. It was found that all selected NTOs add mostly positive posts and in the sample of two hundred contributions there are only seven with negative polarity of sentiment. There was a moderate correlation between customer growth and positive polarity in the contribution. The results show that creating stable positive descriptions for posts can be one of the key variables for the growth of the fan base and stimulation of potential visitors.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    50204 - Business and management

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2020

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Hradec Economic Days

  • ISBN

    978-80-7435-776-3

  • ISSN

    2464-6059

  • e-ISSN

    2464-6067

  • Number of pages

    7

  • Pages from-to

    250-256

  • Publisher name

    Univerzita Hradec Králové

  • Place of publication

    Hradec Králové

  • Event location

    Hradec Králové

  • Event date

    Apr 2, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000568108700027