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Mining and exploring electronic word-of-mouth from Twitter: case of the Java Jazz Festival

Mining and exploring electronic word-of-mouth from Twitter: case of the Java Jazz Festival This paper aims to explore textual patterns in ten years of electronic word-of-mouth communications amongst social media (SM) users of the Java Jazz Festival.Design/methodology/approachThis study uses a data-scraping technique to gather user-generated content from Twitter. Word-cloud and word-frequency analysis, along with descriptive coding and pattern matching, are used to categorise the initial findings. Trends and differences in terms of the number of tweets over a ten-year period were examined using analysis of variance and seasonality analysis.FindingsFrom more than 1.3 million Twitter tweets between 2008 and 2018, this study identified six initial themes. Quantitative analysis revealed that the number of tweets differed significantly in the four quarters of the ten-year period.Research limitations/implicationsThe results of this study contrast with the claim that digital media communication generally occurs before a festival begins and are least during the festival. Nevertheless, this study supports the notion that SM interaction results in positive consequences, drives conversations amongst users and increases engagement.Practical implicationsThis study offers five practical implications for music festival organisers and related entities.Originality/valueTo the best of the author’s knowledge, this study is the first to provide a systematic and practical data mining and interpretation approach from Twitter within a ten-year period in the Asia Pacific context, through the case of the Java Jazz Festival. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Hospitality and Tourism Technology Emerald Publishing

Mining and exploring electronic word-of-mouth from Twitter: case of the Java Jazz Festival

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References (40)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1757-9880
eISSN
1757-9880
DOI
10.1108/jhtt-03-2020-0067
Publisher site
See Article on Publisher Site

Abstract

This paper aims to explore textual patterns in ten years of electronic word-of-mouth communications amongst social media (SM) users of the Java Jazz Festival.Design/methodology/approachThis study uses a data-scraping technique to gather user-generated content from Twitter. Word-cloud and word-frequency analysis, along with descriptive coding and pattern matching, are used to categorise the initial findings. Trends and differences in terms of the number of tweets over a ten-year period were examined using analysis of variance and seasonality analysis.FindingsFrom more than 1.3 million Twitter tweets between 2008 and 2018, this study identified six initial themes. Quantitative analysis revealed that the number of tweets differed significantly in the four quarters of the ten-year period.Research limitations/implicationsThe results of this study contrast with the claim that digital media communication generally occurs before a festival begins and are least during the festival. Nevertheless, this study supports the notion that SM interaction results in positive consequences, drives conversations amongst users and increases engagement.Practical implicationsThis study offers five practical implications for music festival organisers and related entities.Originality/valueTo the best of the author’s knowledge, this study is the first to provide a systematic and practical data mining and interpretation approach from Twitter within a ten-year period in the Asia Pacific context, through the case of the Java Jazz Festival.

Journal

Journal of Hospitality and Tourism TechnologyEmerald Publishing

Published: Jul 15, 2021

Keywords: eWOM; Analytics; Text mining; Music festival; 分析; 音乐节; eWOM; 文本挖掘

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