Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Leveraging User Diversity to Harvest Knowledge on the Social Web   Social web users are a very diverse group with varying interests, levels of
expertise, enthusiasm, and expressiveness. As a result, the quality of content
and annotations they create to organize content is also highly variable. While
several approaches have been proposed to mine social annotations, for example,
to learn folksonomies that reflect how people relate narrower concepts to
broader ones, these methods treat all users and the annotations they create
uniformly. We propose a framework to automatically identify experts, i.e.,
knowledgeable users who create high quality annotations, and use their
knowledge to guide folksonomy learning. We evaluate the approach on a large
body of social annotations extracted from the photosharing site Flickr. We show
that using expert knowledge leads to more detailed and accurate folksonomies.
Moreover, we show that including annotations from non-expert, or novice, users
leads to more comprehensive folksonomies than experts' knowledge alone.

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The categories of this paper are: chem-ph
13
The categories of this paper are: quant-ph
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The categories of this paper are: nucl-ex
14
The categories of this paper are: math-ph
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The categories of this paper are: acc-phys
16
The categories of this paper are: stat
0
The categories of this paper are: hep-ph
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The categories of this paper are: supr-con
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The categories of this paper are: cond-mat
8
The categories of this paper are: hep-ex
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The categories of this paper are: econ
12
The categories of this paper are: nucl-th
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The categories of this paper are: eess
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The categories of this paper are: math
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The categories of this paper are: bayes-an
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The categories of this paper are: astro-ph