An artist ranking system based on social media mining
| Autor: | Amalia F. Foka |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer science
business.industry media_common.quotation_subject Rank (computer programming) Qualitative property Library and Information Sciences Public opinion Data science Social media mining Feeling Pattern recognition (psychology) Social media Brand equity business Information Systems media_common |
| Zdroj: | Information Retrieval Journal. 21:410-448 |
| ISSN: | 1573-7659 1386-4564 |
| Popis: | Currently users on social media post their opinion and feelings about almost everything. This online behavior has led to numerous applications where social media data are used to measure public opinion in a similar way as a poll or a survey. In this paper, we will present an application of social media mining for the art market. To the best of our knowledge, this will be the first attempt to mine social media to extract quantitative and qualitative data for the art market. Although there are previous works on analyzing and predicting other markets, these methodologies cannot be applied directly to the art market. In our proposed methodology, artists will be treated as brands. That is, we will mine Twitter posts that mention specific artists’ names and attempt to rank artists in a similar manner as brand equity and awareness would be measured. The particularities of the art market are considered mainly in the construction of a topic-specific user network where user expertise and influence is evaluated and later used to rank artists. The proposed ranking system is evaluated against two other available systems to identify the advantages it can offer. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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