Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Aggregating Content and Network Information to Curate Twitter User Lists   Twitter introduced user lists in late 2009, allowing users to be grouped
according to meaningful topics or themes. Lists have since been adopted by
media outlets as a means of organising content around news stories. Thus the
curation of these lists is important - they should contain the key information
gatekeepers and present a balanced perspective on a story. Here we address this
list curation process from a recommender systems perspective. We propose a
variety of criteria for generating user list recommendations, based on content
analysis, network analysis, and the "crowdsourcing" of existing user lists. We
demonstrate that these types of criteria are often only successful for datasets
with certain characteristics. To resolve this issue, we propose the aggregation
of these different "views" of a news story on Twitter to produce more accurate
user recommendations to support the curation process.

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The categories of this paper are: econ
27
The categories of this paper are: comp-gas
25
The categories of this paper are: patt-sol
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The categories of this paper are: hep-ex
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The categories of this paper are: solv-int
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The categories of this paper are: nucl-ex
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The categories of this paper are: eess
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The categories of this paper are: q-fin
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The categories of this paper are: funct-an
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The categories of this paper are: q-alg
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The categories of this paper are: atom-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: hep-lat
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The categories of this paper are: math-ph
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The categories of this paper are: stat
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The categories of this paper are: nlin