Social tagging systems have established themselves as an important part in today's web and have attracted the interest of our research community in a variety of investigations. This has led to several assumptions about tagging, such as that tagging systems exhibit a social component. In this work we overcome the previous absence of data for testing such an assumption. We thoroughly study social interaction, leveraging for the first time live log data gathered from the real-world public social tagging system BibSonomy. Our results indicate that sharing of resources constitutes an important and indeed social aspect of tagging.
The representation and retrieval of books on the Skoob and GoodReads platforms is explored. In order to investigate the procedures and criteria of social indexing in the book platforms of Skoob and GoodReads, exploratory research was carried out in two phases: bibliographical research on social indexing, and analysis of the attribution and retrieval of representative terms in the book platforms of Skoob and GoodReads. The research results showed that both platforms offer the same basic services: organizing the users' readings and enabling interaction between them regarding their readings. What sets them apart are small details: GoodReads does not allow social indexing, although users can assign representative terms to the books that make up their personal shelf; on Skoob, the users perform the social indexing. Both platforms do not have any type of controlled vocabulary, directly affecting the representation and retrieval of books.
Authors focus on Flickr and Last.fm, two social media systems in which we can relate the tagging activity of the users with an explicit representation of their social network
By collectiong a set of US partisan Republican and Democratic videos, it is investigated how TikTok users communicate with each other about political issues
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