Semantic Emergence From Social Tagging Systems

Semantic Emergence From Social Tagging Systems

Mohammed Alruqimi (Abdelmalek Essaadi University, Tetouan, Morocco) and Noura Aknin (Abdelmalek Essaadi University, Tetouan, Morocco)
DOI: 10.4018/IJOCI.2015010102
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Recently, Social tagging systems (folksonomies) have become very popular platforms where content is created collaboratively by users. This kind of environments allows users to assign shared resources with freely chosen keywords (tags). Folksonomies provide a valuable addition to the knowledge organization methods since they allow users to choose vocabularies that meet their real tastes and cognition. However, the lacking of standardization and the flat structure of tags in folksonomies pose challenges for folksonomy searching and information retrieval. Several researches have been proposed to overcome these drawbacks. In this paper, the authors present, describe and compare the most relevant approaches to capturing hidden semantics in folksonomies and turning it into ontologies. The authors also present and describe many techniques, tools and online resources that can be useful in working on such systems. Finally, the authors propose an approach to extract ontology from social tagging systems.
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Social Tagging Systems (Folksonomies)

Folksonomy is a user-generated classification system of web contents. It is also known as collaborative tagging and social tagging. Folksonomy-base systems allow users to tag web resources (videos, images, links and etc.) with their chosen words or phrases. Social tagging systems consist of at least three set of elements: tagger, digital objects and tags. Taggers are the persons who interact within the closed community. Digital objects are the shared resources, and tags which are used for describing shared resources. (Thielen, et al, 2010)

Folksonomy term is coined by Thomas Vander Wal, derived from folk and taxonomy. Vander Wal identified two types of folksonomy: broad and narrow. In broad folksonomy (such as Delicious), many users tag particular content with their own vocabularies, thus creating a greater amount of metadata for that content. In narrow folksonomy (such as Flicker), few users tag an object with a limited number of terms which used to get back to the object. (Vander Wal, 2005)

  • Definition 1:

  • A folksonomy is a tuple F: = (U, T, R, Y) where:

  • U is a finite set of users,

  • T is a finite set of tags,

  • R is a finite set of resources, and Y is a ternary relation between them, i. e., Y ⊆ U ×T × R, whose elements are called tag assignments.

Figure 1.

Model of tagging system (adapted from Weller et al, 2011)


Folksonomies are a cheap method of documents indexing and describing the masses of information on the web, it has proven a powerful alternative to existing top-down categorization techniques, such as taxonomies or predefined dictionaries due to its flexibility. (Wetzker et al, 2010) Folksonomy-based systems allow users to generate the content and classify it in their own way based on their individual own experience, linguistic styles and preferences without relying on a previously defined terms, which reduces the required cognitive efforts. On other hand, this freedom in the choice of vocabularies as tags leads to many problems such as ambiguity and lack of standardization. However, handling these problems will contribute much in improving information retrieval, recommendations and etc.

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