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Title:
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EXAMINATION OF SOCIAL MEDIA GUIDELINES AT UNIVERSITIES IN JAPAN USING AN ARTIFICIAL NEURAL NETWORK |
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Author(s):
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Yukiko Maruyama, Ryozo Kitajima and Ryotaro Kamimura |
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ISBN:
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978-989-8533-69-2 |
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Editors:
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Pedro Isaías and Hans Weghorn |
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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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Social media guidelines, affordance approach, artificial neural network, potential learning |
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Type:
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Short Paper |
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First Page:
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283 |
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Last Page:
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288 |
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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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Social media guidelines are complex because they are written in natural language. We adopted the affordance approach and a new type of artificial neural network called potential learning (PL) to classify social media guidelines. As a result, the affordance editability was extracted as an important variable. It appears that editability characterizes university guidelines. The conventional method, however, could not be used to classify the guidelines. Therefore, PL is a useful method to analyze data written in natural language such as social media guidelines. |
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