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Title:
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SOCIAL NETWORKS KNOWLEDGE DISCOVERY FOR THE DEVELOPMENT OF DIGITAL REGIONS |
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Author(s):
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Yaroslav Milchuk, Alla Kravets |
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ISBN:
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978-989-8533-60-9 |
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Editors:
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Piet Kommers and Pedro Isaías |
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Year:
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2017 |
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Edition:
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Single |
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Keywords:
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Digital Region, Knowledge Discovery, Social Behavior, Forecasting Of Social Preferences, Implicit Social Graph, Geoformation Model, Egovernment |
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Type:
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Full Paper |
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First Page:
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113 |
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Last Page:
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120 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The information obtained from social networks analysis is one of the most reliable sources of knowledge that could be used in regional development management. The number of people who use different social networking services is increasing year by year, the social network audience includes different age groups. More and more profiles in social networks are becoming open. The article describes the concept of digital region - regional development management based on social behavior and social preferences analysis. A model based on social preferences of people visiting certain social places is described. The model is used for identification of social preferences and building a geo-information model. The data were collected in social nets VKontakte, Facebook, Twitter, LinkedIn by questionnaires and were an alyzed by knowledge mining method based on the algorithm for modeling of the implicit social graph of users interests, providing a complete scheme of social data of the user. The algorithm is based on data obtained from HTML code of social network and the information selected from key tags. Implementation of the described models and algorithms in regional development management system is described. |
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