Abstract
Social networking sites like Flickr, YouTube and Del.icio.us have been gaining more popularity on the internet. Users can create, evaluate, and distribute the information over the internet with the change of web to a medium. A social tagging system allows users to share sources and enlighten them with different descriptive tags. Folksonomy is a contribution of social tagging. It allows users to tag online content/resource for common accessibility and resource searching. Users can freely type any form of text or keywords when tagging a resource. The reason behind popularity of folksonomy applications is all users create tags without having any technological skills and experience. With the social tagging simplicity, it can gather huge amount of user contributed tags. Tag sets can also be generated with the help of different online websites. Different relationships like similarity, co-occurrence etc. appears among tags of folk tag set. In this work, we have tested that whether the relationships that exists in folk tag sets are also present in the tag sets generated by automatic tools. For our testing, we took five automatic tag set generating websites, which includes To cloud, Word It Out, Tag crowd, Word sift and Word Art. The result of this work helps to conclude the semantic richness of tag set generated by automatic tools.
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Shafique, F., Khan, M., Jabeen, F., Sanila (2019). Semantic Richness of Tag Sets: Analysis of Machine Generated and Folk Tag Set. In: Silhavy, R. (eds) Software Engineering Methods in Intelligent Algorithms. CSOC 2019. Advances in Intelligent Systems and Computing, vol 984. Springer, Cham. https://doi.org/10.1007/978-3-030-19807-7_4
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DOI: https://doi.org/10.1007/978-3-030-19807-7_4
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