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Title:
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APPLICATIONS OF CLASSIFICATION ALGORITHMS FOR ANALYSIS OF FACTORS WHICH INFLUENCE THE PREDICTION OF THE IMPACT FACTOR ON SOCIAL NETWORKS |
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Author(s):
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Marco Aurélio Schünke, Dante Augusto Couto Barone |
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ISBN:
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978-989-8533-57-9 |
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Editors:
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Pedro Isaías |
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Year:
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2016 |
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Edition:
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Single |
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Keywords:
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Prediction, Data Mining, Social Networks |
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Type:
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Poster/Demonstration |
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First Page:
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315 |
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Last Page:
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317 |
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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 dissemination of advertisements on social networks has grown tremendously in recent years, but is not always possible to evaluate factors that influence the impact of interactions through advertising. Companies as Google and Facebook are on the list of the largest companies in the world. Investment on advertising and pages creation for dissemination of advertisements and brands has led Facebook to an outstanding position in this scenario. In this context, this study aims to analyze and predict the number of interactions in news published in five fan pages, which are the most accessed at the Facebook social network in Brazil. As a contribution is proposed to determine the impact factor of publications, considering the average of three mentioned features, the number of likes, the number of comments and the number of times that the news was shared. Results of different techniques of classification will be evaluated, beyond the influence of characteristics related to words and more frequent terms. |
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