Exploring Temporal Analysis of Tweet Content from Cultural Events

Quillot, Mathias; Ollivier, Cassandre; Dufour, Richard; Labatut, Vincent

doi:10.1007/978-3-319-68456-7_7

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…Thus, future research should address the following: how the patterns manifest in different SM, not only Twitter, and how they are aggregated amongst different platforms; how other qualitative and quantitative techniques can be used to produce qualitative patterns (e.g. natural language processing using NLTK library, social network analysis, Bayesian network, semantic analysis, temporal embedding or the Word2Vec approaches (Quillot et al , 2017); how collaboration between event management, marketing and computer science scholars can produce code and programmes in open-source programming software to generate meaningful information from complex and unstructured data through a more streamlined process on various SM platforms. Such data could include what people talk about before, during and after a festival, what the artist line-up should be for the subsequent year’s festival based on the eWOM data, what people say about the festival on different SM platforms; and what factors potentially influence different tweet frequencies and trends before, during and after a festival. …”

Section: Discussionmentioning

confidence: 99%

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

Saragih

2021

JHTT

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Purpose 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/approach This 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. Findings From 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/implications The 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 implications This study offers five practical implications for music festival organisers and related entities. Originality/value To 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.

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Section: Discussionmentioning

confidence: 99%

“…how other qualitative and quantitative techniques can be used to produce qualitative patterns (e.g. natural language processing using NLTK library, social network analysis, Bayesian network, semantic analysis, temporal embedding or the Word2Vec approaches (Quillot et al , 2017);…”

Section: Discussionmentioning

confidence: 99%

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

Saragih

2021

JHTT

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The COVID-19 Pandemic as Catalyst for Virtual Events

Pop¹,

Marian-Potra²,

Hognogi³

2023

JSSP

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Globally, the effects of the COVID-19 pandemic have affected the cultural sector the most by restricting, suspending, and cancelling events in physical spaces. In Romania, the occurrence of the first COVID-19 infected case and the gradual restriction of the public to events until their complete stop during emergency and alert periods led to the reorientation of cultural spaces to online audiences through social media. The present study focuses on the evolution of online events organized by the independent cultural and creative industry during the emergency state of the pandemic crisis (February 27 – May 14, 2020). The types of spaces and the perception of cultural professionals were considered in the analysis, at the city level. The independent creative communities of two of the most effervescent cultural cities in Romania (Timişoara and Cluj-Napoca) readjusted their cultural activity, by organizing online events. A mixed method of analysis was used, in which two methods of data collection were employed: some 205 events recorded on different social media pages (YouTube, Facebook, Instagram) were collected and in-depth interviews with relevant representatives of the independent cultural and creative industry were conducted. Descriptive statistics were used to describe the qualitative data. Results showed an openness of artists to the virtual environment and a relocation of events from the physical to the online environment, a readjustment of events for the virtual audience through creativity.

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Semi-automatic generation of semantic dendrograms for the identification of themes in Twitter events

Abascal-Mena

Lopez-Ornelas

2018

IFS

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Exploring Temporal Analysis of Tweet Content from Cultural Events

Cited by 3 publications

References 8 publications

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

The COVID-19 Pandemic as Catalyst for Virtual Events

Semi-automatic generation of semantic dendrograms for the identification of themes in Twitter events

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