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- Individuals often imitate each other to fall into the typical group, leading to a self-organized state of typical behaviors in a community. In this paper, we model self-organization in social tagging systems and illustrate the underlying interaction and dynamics. Specifically, we introduce a model in which individuals adjust their own tagging tendency to imitate the average tagging tendency. We found that when users are of low confidence, they tend to imitate others and lead to a self-organized state with active tagging. On the other hand, when users are of high confidence and are stubborn to change, tagging becomes inactive. We observe a phase transition at a critical level of user confidence when the system changes from one regime to the other. The distributions of post length obtained from the model are compared to real data, which show good agreement.
- With the emergence of Web 2.0, social tagging systems become highly popular in recent years and thus form the so-called folksonomies. Personalized tag recommendation in social tagging systems is to provide a user with a ranked list of tags for a specific resource that best serves the user's needs. Many existing tag recommendation approaches assume that users are independent and identically distributed. This assumption ignores the social relations between users, which are increasingly popular nowadays. In this paper, we investigate the role of social relations in the task of tag recommendation and propose a personalized collaborative filtering algorithm. In addition to the social annotations made by collaborative users, we inject the social relations between users and the content similarities between resources into a graph representation of folksonomies. To fully explore the structure of this graph, instead of computing similarities between objects using feature vectors, we exploit the method of random-walk computation of similarities, which furthermore enable us to model a user's tag preferences with the similarities between the user and all the tags. We combine both the collaborative information and the tag preferences to recommend personalized tags to users. We conduct experiments on a dataset collected from a real-world system. The results of comparative experiments show that the proposed algorithm outperforms state-of-the-art tag recommendation algorithms in terms of prediction quality measured by precision, recall and NDCG.
- 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.
- Na početku ovog rada govori se o povijesti društvenog čitanja, s kojom svrhom se odvija, zašto je bitno u današnjici kakvu poznajemo te u kojem trenutku čitanje zapravo postaje društveno. U nastavku se navode različiti oblici društvenog čitanja, prikazuje se kako je tehnologija utjecala na njihov razvoj i prednosti koje nosi pojava virtualnih čitateljskih klubova nastalih pod utjecajem tehnologije. Nakon toga slijedi poglavlje u kojem se govori o društvenom označavanju i oznakama koje su jedan od tri sastavna dijela samog procesa društvenog označavanja. Govori se i o različitom ponašanju korisnika prilikom procesa društvenog označavanja, bez kojih taj isti proces isto ne bi bio moguć. Zatim se navode i objašnjavaju prednosti i nedostatci navedenog procesa te zašto je uopće važno uključiti korisnike u organizaciju izvora znanja. Pojam folksonomije uvodi se u idućem poglavlju, kao i tri vrste folksonomije koje možemo razlikovati. Objašnjava se pojam ''cloud tag'', pojam uske i široke folksonomije te zadatak iste. Potom su kao primjer društvenog označavanja pobliže opisani mrežni sustavi LibraryThing i Goodreads kroz navođenje osnovnih informacija o funkcioniranju istih kao i katalogizaciji te uporabi oznaka na ovim mrežnim sustavima, te zaključno čime uporaba oznaka rezultira i kolika je sličnost ova dva sustava za društveno označavanje.
- Rad se bavi ulogom društvenog označivanja (social tagging) u pretraživanju web kataloga i razlikama takvoga načina klasifikacije u odnosu na uobičajene kontrolirane rječnike koje koristi većina knjižnica. U prvome dijelu rada donosi se kratak pregled povijesnoga razvoja knjižničnih kataloga. Središnji dio opisuje teorijsko utemeljenje koncepta društvenoga označivanja i njemu srodnog pojma folksonomije. U završnome dijelu analizira se primjena društvenoga označivanja u praksi, na primjerima odabranih kataloga narodnih knjižnica.
- In 2009, Kaite Stover examined the expansion of readercentered social networking sites and what she called “the wild appeal factor” (see “Stalking the Wild Appeal Factor,” Reference & User Services Quarterly 48, no. 3 [Spring 2009]: 243–46). Stover looked at several then-new sites that might be of interest to readers’ advisors, particularly in terms of how readers talk about books and reading in their own words. As Stover pointed out, the conversation about books is taking place on the web in a variety of forms, and as reflective practitioners, we need to be aware of those conversations happening outside the library walls. In this issue’s column, Yesha Naik expands on this discussion by looking at how members of one bibliocentric social networking site, Goodreads.com, talk with each other and the broader reading community about books and reading. Yesha looks at reader discussions of titles in five diverse genres and what we learn from those discussions about reader interests. She then moves from this examination to explore how readers’ advisors might take advantage of this knowledge in their daily practice. Librarianship is Yesha’s third career, but she finds that her previous incarnations as middle school teacher and college admissions counselor have well-prepared her for working as a YA librarian in a bustling neighborhood branch of Brooklyn Public Library. A 2011 graduate of the Queens College GSLIS, her professional fascinations include readers’ advisory, teen and children’s services, diversity in YA literature, and serving immigrant populations in the public library setting.
- Goodreads je internetska stranica osnovana 2007. godine koja povezuje korisnike oko knjiga. Radi se o svojevrsnoj društvenoj mreži za čitatelje. U ovom se radu istražuje savjetuju li se međusobno korisnici o knjigama putem recenzija knjiga koje pišu korisnici tog servisa iz grupe koja okuplja članove iz Hrvatske. Osim otkrivanja povezanosti pisanja prikaza i savjetovanja na Goodreadsu, odnosno reakcija korisnika na ponuđene preporuke i savjete od strane drugih korisnika, dodatni je cilj otkrivanje termina za opis privlačnosti knjiga (eng. appeal) koji korisnici Goodreadsa iz Hrvatske koriste u svojim prikazima. Za postizanje ovih ciljeva, u istraživanju je korištena metoda analize sadržaja za analizu recenzija i otkrivanje korištenih termina privlačnosti. Za dobivanje uvida u osobne stavove i navike korisnika iz Hrvatske na Goodreadsu koji se tiču čitanja i pisanja prikaza knjiga koristila se metoda ankete. Na temelju rezultata istraživanja, oblikovani su prijedlozi knjižničarima kako oni sami mogu iskoristiti prednosti ove stranice u vlastitom radu, poglavito što se tiče usluge savjetovanja čitatelja.
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