| Autor: |
Taeha Yi, Po Yan Lai, Mi Chang, Sukjoo Hong, Ji-Hyun Lee |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
KAIST Research Series ISBN: 9789811577062 |
| DOI: |
10.1007/978-981-15-7707-9_4 |
| Popis: |
To better serve visitors with digital means, museums must understand visitors and their needs. Previous studies investigated the needs and visitor–museum interactions mainly by observation and survey. However, these approaches offer limited insights into the interactions which can be hard to observe if happen beyond the museum space. Nowadays, data that tracks the museum visitors become obtainable on social media platforms. The goal of this study is to classify types and behavior patterns of art museum visitors making use of social networking data. Data collection started with the five most followed Korean art museums on the social networking service Instagram. We sampled 5000 followers from their official accounts and collected all hashtags used by these users. Our findings show that Korean art museum visitors exhibited different characteristics and behavior patterns. Users can be clustered into six groups based on their network modularity. This paper describes how the six groups are different in terms of their social network features and hashtags. The study demonstrates how social network analysis techniques can be employed in visitor research. The results also have real-world implications and set the basis for future research in a real-world setting. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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