Collective Classification of Social Network Spam
Unsolicited messages affects virtually every popular social media website, and spammers have become increasingly proficient at bypassing conventional filters, prompting a stronger effort to develop new methods. First, we build an independent model using features that capture the cases where spam is...
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| Language: | en_US |
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University of Oregon
2017
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| Online Access: | http://hdl.handle.net/1794/22625 |