D12-1006 |
Social Networks Most of the work on
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social networks
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analysis has only focused on
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D11-1053 |
2005 ) to model interactions in
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social networks
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. The model was fitted to small
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D10-1121 |
research efforts to examine signed
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social networks
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in more detail . It will also
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D10-1121 |
method allows to extract signed
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social networks
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from multi-party online discussions
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D12-1006 |
Dataset . We built one signed
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social network
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for every domain ( e.g. politics
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D12-1006 |
data such as email headers for
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social network
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construc - tion . Gruzd and Hyrthonthwaite
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D12-1006 |
automatically constructing a signed
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social network
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representation of discussions
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D11-1053 |
in collaborative filtering and
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social networks
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as special cases . The matrix
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D11-1052 |
analyzing sentiment in microblogs and
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social networks
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, whether for research or commercial
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D10-1121 |
different from most of the research on
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social networks
|
that has focused almost exclusively
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D12-1006 |
automate the discovery of signed
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social networks
|
using the text embedded in the
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D10-1121 |
clearly important , most of the
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social networks
|
research has focused only on
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D10-1121 |
Even though using signed edges in
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social network
|
studies is clearly important
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D09-1029 |
NETWORK such as Computer network ,
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Social network
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, Telecommunications network
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D12-1006 |
from text , and analyzing signed
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social networks
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. We define our problem and explain
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D09-1162 |
information in news articles ,
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social networks
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( Tsai et al. , 2009 ) , and
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et al. ( 2010b ) study signed
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social networks
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generated from Slashdot , Epinions
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D10-1121 |
efforts that go beyond standard
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social network
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analysis that is based on positve
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the fact that we extract signed
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social networks
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with both positive and negative
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D11-1053 |
well as graph structure in the
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social network
|
between reviewers ( Lu et al.
|