Investigating Users’ Tagging Behavior in Online Academic Community Based on Growth Model: Difference between Active and Inactive Users
| Autor: | Duanning Zhou, Yunhong Xu, Dehu Yin |
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| Rok vydání: | 2018 |
| Předmět: |
Computer Networks and Communications
Computer science 05 social sciences Context (language use) 02 engineering and technology Growth model Affect (psychology) Social relation Theoretical Computer Science World Wide Web 020204 information systems 0502 economics and business 0202 electrical engineering electronic engineering information engineering Academic community 050211 marketing Software Information Systems Multinomial logistic regression |
| Zdroj: | Information Systems Frontiers. 21:761-772 |
| ISSN: | 1572-9419 1387-3326 |
| Popis: | With the development of social interaction techniques and social tagging mechanisms, online academic community as a new platform has greatly changed the way users organize and share knowledge. The large amount of social tagging data occurred on online academic community provides us a channel to systematically understand users’ tagging behavior. Based on data collected from a specific online academic community, this research first classifies users into two categories: active and inactive users. After that, growth models (damped exponential model, normal model and fluctuating model) are employed to investigate tagging behavior for both active and inactive users. Factors that might influence the likelihood of the growth models are also identified based on multinomial logistic regression. This research expands our understanding on users’ tagging behavior and factors that may affect their tagging behavior in the context of online academic community. |
| Databáze: | OpenAIRE |
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