Profiling Social Networks: A Social Tagging Perspective

Ding, Ying; Jacob, Elin K.; Caverlee, James; Fried, Michael; Zhang, Zhixiong

doi:10.1045/march2009-ding

Cited by 15 publications

(7 citation statements)

References 10 publications

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“…Based on a review of the 1,300 most frequently assigned tags in the combined set of tags from Delicious, Flickr, and YouTube for the years 2005, 2006, and 2007, certain tagging behaviors were identified (see Table 8; for an alphabetical listing of all 1,300 tags, see Ding et al, 2009). For example, taggers often date objects by assigning tags for the current year or month; this is especially prevalent in Flickr, where the current year is always among the top-ranked tags (see Table 6).…”

Section: Tagging Patternsmentioning

confidence: 99%

Perspectives on social tagging

Ding

Jacob

Zhang

et al. 2009

J. Am. Soc. Inf. Sci.

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Social tagging is one of the major phenomena transforming the World Wide Web from a static platform into an actively shared information space. This paper addresses various aspects of social tagging, including different views on the nature of social tagging, how to make use of social tags, and how to bridge social tagging with other Web functionalities; it discusses the use of facets to facilitate browsing and searching of tagging data; and it presents an analogy between bibliometrics and tagometrics, arguing that established bibliometric methodologies can be applied to analyze tagging behavior on the Web. Based on the Upper Tag Ontology (UTO), a Web crawler was built to harvest tag data from Delicious, Flickr, and YouTube in September 2007. In total, 1.8 million objects, including bookmarks, photos, and videos, 3.1 million taggers, and 12.1 million tags were collected and analyzed. Some tagging patterns and variations are identified and discussed.

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Section: Tagging Patternsmentioning

confidence: 99%

Perspectives on social tagging

Ding

Jacob

Zhang

et al. 2009

J. Am. Soc. Inf. Sci.

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“…Refactoring is a programming practice in which we look at a computer system, identify parts that are confusing, inefficient, or redundant, and then systematically improve them—all while making sure that the functions of the program do not change (Hendler, 2007 ; Ding et al, 2009 ). We propose a refactoring of the scholarly journal system.…”

Section: Introductionmentioning

confidence: 99%

Decoupling the scholarly journal

Priem

Hemminger

2012

Front. Comput. Neurosci.

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Although many observers have advocated the reform of the scholarly publishing system, improvements to functions like peer review have been adopted sluggishly. We argue that this is due to the tight coupling of the journal system: the system's essential functions of archiving, registration, dissemination, and certification are bundled together and siloed into tens of thousands of individual journals. This tight coupling makes it difficult to change any one aspect of the system, choking out innovation. We suggest that the solution is the “decoupled journal (DcJ).” In this system, the functions are unbundled and performed as services, able to compete for patronage and evolve in response to the market. For instance, a scholar might deposit an article in her institutional repository, have it copyedited and typeset by one company, indexed for search by several others, self-marketed over her own social networks, and peer reviewed by one or more stamping agencies that connect her paper to external reviewers. The DcJ brings publishing out of its current seventeenth-century paradigm, and creates a Web-like environment of loosely joined pieces—a marketplace of tools that, like the Web, evolves quickly in response to new technologies and users' needs. Importantly, this system is able to evolve from the current one, requiring only the continued development of bolt-on services external to the journal, particularly for peer review.

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“…Like a great number of online social networks, social tagging networks are considered as evolving and providing more and more information over time. (Ding et al, 2009) analysed tags frequencies across time and found that changing trends in user's interests can be identified and tracked over time. To extract the relevant information from this kind of data, we have to take into account this dynamic characteristic (see section 2.3).…”

Section: Tag-based User Profilingmentioning

confidence: 99%

“…For new or less-active users that interact less frequently with the system, their profile can be empty or does not contain any useful interests for a mechanism of customization or recommendation. Several works (Tchuente et al, 2013) (Carmel et al, 2009) (Ding et al, 2009) propose to use information from user's social networks.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Two Egocentric-based User Profiling Algorithms - Experiment in Delicious

Canut

Mezghani

On-At

et al. 2015

Proceedings of the 17th International Conference on Enterprise Information Systems

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With the growing amount of social media contents, the user needs more accurate information that reflects his interests. We focus on deriving user's profile and especially user's interests, which are key elements to improve adaptive mechanisms in information systems (e.g. recommendation, customization). In this paper, we are interested in studying two approaches of user's profile derivation from egocentric networks: individual-based approach and community-based approach. As these approaches have been previously applied in a co-author network and have shown their efficiency, we are interested in comparing them in the context of social annotations or tags. The motivation to use tagging information is that tags are proved relevant by many researches to describe user's interests. The evaluation in Delicious social databases shows that the individual-based approach performs well when the semantic weight of user's interests is taken more in consideration and the community-based approach performs better in the opposite case. We also take into consideration the dynamic of social tagging networks. To study the influence of time in the efficiency of the two user's profile derivation approaches, we have applied a time-awareness method in our comparative study. The evaluation in Delicious demonstrates the importance of taking into account the dynamic of social tagging networks to improve effectiveness of the tag-based user profiling approaches.

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Profiling Social Networks: A Social Tagging Perspective

Cited by 15 publications

References 10 publications

Perspectives on social tagging

Perspectives on social tagging

Decoupling the scholarly journal

A Comparative Study of Two Egocentric-based User Profiling Algorithms - Experiment in Delicious

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