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A real-time social network-based knowledge discovery system for decision making

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dc.creator YÜKSEL, Asım Sinan
dc.creator Tan, Fatma Gulsah
dc.date 2017-12-31T21:00:00Z
dc.date.accessioned 2020-10-06T10:24:54Z
dc.date.available 2020-10-06T10:24:54Z
dc.identifier 613dabb7-68c1-435a-bf89-bcbef10a30b3
dc.identifier 10.1080/00051144.2018.1531214
dc.identifier https://avesis.sdu.edu.tr/publication/details/613dabb7-68c1-435a-bf89-bcbef10a30b3/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/61613
dc.description The increasing amount of data in social networks has complicated data processing and interpretation. Therefore, intelligent decision-support mechanisms that have the ability to automatically extract meaning from data and interpret the opinions of people in real time have become inevitable. In this study, an intelligent multilingual decision support system was implemented, and a new algorithm that employs text mining and sentiment analysis techniques was developed to automatically interpret the opinions of social network users about the places they plan to visit. The system can be used as a baseline for sentiment analysis in social networks and can be adapted to build new systems. In this study, we set our main focus on Turkish language and show the applicability of our approach for other languages through the experiments for English language. The dataset required for the implementation of text mining techniques was created based on the venue recommendations shared on Foursquare social media platform. As a result, a contribution was made to the way the social network users make decisions without reading thousands of recommendations. Our results show that the developed system achieves classification accuracy of 84.49% for Turkish and 95% for English. Finally, the most liked or disliked foods/beverages are correctly identified for 107 out of 128 venues.
dc.language eng
dc.rights info:eu-repo/semantics/closedAccess
dc.title A real-time social network-based knowledge discovery system for decision making
dc.type info:eu-repo/semantics/article


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