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 <channel rdf:about="http://ebiquity.umbc.edu/tag/spam/">
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    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/461/Ensembles-in-Adversarial-Classification-for-Spam"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/371/The-Information-ecology-of-social-media-and-online-communities"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/408/Spings-und-Splog"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/373/Detecting-Spam-Blogs-An-Adaptive-Online-Approach"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/362/Spam-in-Blogs-and-Social-Media-Tutorial-"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/342/Towards-Spam-Detection-at-Ping-Servers"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/326/BlogVox-Separating-Blog-Wheat-from-Blog-Chaff"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/318/Blog-Track-Open-Task-Spam-Blog-Classification"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/296/Detecting-Spam-Blogs-A-Machine-Learning-Approach"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/299/Characterizing-the-Splogosphere"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/269/SVMs-for-the-Blogosphere-Blog-Identification-and-Splog-Detection"/>
    <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/227/On-Leveraging-Social-Media"/>
    <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/241/spam-in-blogs-and-social-media"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/296/Adversarial-Classification-An-Ensemble-based-approach"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/212/Detecting-Spam-Blogs-An-Adaptive-Online-Approach-"/>
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 <image rdf:about="http://ebiquity.umbc.edu/img/logo.jpg">
  <title>UMBC ebiquity research group</title>
  <link>http://ebiquity.umbc.edu</link>
  <url>http://ebiquity.umbc.edu/img/logo.jpg</url>
 </image>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/461/Ensembles-in-Adversarial-Classification-for-Spam">
  <title><![CDATA[Ensembles in Adversarial Classification for Spam]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/461/Ensembles-in-Adversarial-Classification-for-Spam</link>
  <description><![CDATA[The standard method for combating spam, either in email or on the web, is to train a classifier on manually labeled instances. As the spammers change their tactics, the performance of such classifiers tends to decrease over time. Gathering and labeling more data to periodically retrain the classifier is expensive. We present a method based on an ensemble of classifiers that can detect when its performance might be degrading and retrain itself, all without manual intervention.  Experiments wit...]]></description>
  <dc:date>2009-11-02</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/371/The-Information-ecology-of-social-media-and-online-communities">
  <title><![CDATA[The Information ecology of social media and online communities]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/371/The-Information-ecology-of-social-media-and-online-communities</link>
  <description><![CDATA[Social media systems such as weblogs, photo- and link-sharing sites, wikis and on-line forums are currently thought to produce up to one third of new Web content.  One thing that sets these ``Web 2.0'' sites apart from traditional Web pages and resources is that they are intertwined with other forms of networked data.  Their standard hyperlinks are enriched by social networks, comments, trackbacks, advertisements, tags, RDF data and metadata.  We describe recent work on building systems that ...]]></description>
  <dc:date>2008-09-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/408/Spings-und-Splog">
  <title><![CDATA[Spings und Splog]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/408/Spings-und-Splog</link>
  <dc:date>2008-05-31</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/373/Detecting-Spam-Blogs-An-Adaptive-Online-Approach">
  <title><![CDATA[Detecting Spam Blogs: An Adaptive Online Approach]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/373/Detecting-Spam-Blogs-An-Adaptive-Online-Approach</link>
  <description><![CDATA[Weblogs, or blogs, are an important new way to publish information, engage in discussions, and form communities on the Internet. Blogs are a global phenomenon, and with numbers well over 100 million they form the core of the emerging paradigm of Social Media. While the utility of blogs is unquestionable, a serious problem now afflicts them, that of spam. Spam blogs, or splogs are blogs with auto-generated or plagiarized content with the sole purpose of hosting profitable contextual ads and/or...]]></description>
  <dc:date>2007-12-10</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/362/Spam-in-Blogs-and-Social-Media-Tutorial-">
  <title><![CDATA[Spam in Blogs and Social Media, Tutorial]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/362/Spam-in-Blogs-and-Social-Media-Tutorial-</link>
  <description><![CDATA[Spam on the Internet dates back over a decade, with its earliest known appearance as an email about the infamous MAKE.MONEY.FAST. campaign. Spam has co-evolved with Internet applications and is now quite common on the World-Wide Web.


As social media systems such as blogs, wikis and bookmark sharing sites have emerged, spammers have quickly developed techniques to infect them as well. The very characteristics underlying the Web, be it version 1.0, 2.0 or 3.0, also enable new varieties o...]]></description>
  <dc:date>2007-03-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/342/Towards-Spam-Detection-at-Ping-Servers">
  <title><![CDATA[Towards Spam Detection at Ping Servers]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/342/Towards-Spam-Detection-at-Ping-Servers</link>
  <description><![CDATA[Spam blogs, or splogs, are blogs featuring plagiarized or auto-generated content. They create link farms to promote affiliates, and are motivated by the profitability of hosting ads. Splogs infiltrate the blogosphere at ping servers, systems that aggregate blog update pings. Over the past year, our work has focused on detecting and eliminating splogs. As techniques used by spammers have evolved, we have learned how splog signatures are tied to tools that create them, that they are beginning t...]]></description>
  <dc:date>2007-03-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/326/BlogVox-Separating-Blog-Wheat-from-Blog-Chaff">
  <title><![CDATA[BlogVox: Separating Blog Wheat from Blog Chaff]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/326/BlogVox-Separating-Blog-Wheat-from-Blog-Chaff</link>
  <description><![CDATA[Blog posts are often informally written, poorly structured, rife with
spelling and grammatical errors, and feature non-traditional
content. These characteristics make them difficult to process with
standard language analysis tools.  Performing linguistic analysis on
blogs is plagued by two additional problems: (i) the presence of spam
blogs and spam comments and (ii) extraneous non-content including
blog-rolls, link-rolls, advertisements and sidebars. We describe
techniques designed to...]]></description>
  <dc:date>2007-01-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/318/Blog-Track-Open-Task-Spam-Blog-Classification">
  <title><![CDATA[Blog Track Open Task: Spam Blog Classification]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/318/Blog-Track-Open-Task-Spam-Blog-Classification</link>
  <description><![CDATA[Spam blogs or Splogs are blogs created for the sole purpose of hosting
ads, promoting affiliate sites and getting new content indexed, with
auto-generated or plagiarized content from other sources. Spammers
equipped with readily available splog creation software inundate the
blogosphere both at ping servers, and at systems that index and
analyze blogs. Our own studies estimate these numbers to be around 75%
at ping servers and 20% at popular blog search engines. In this open
submission...]]></description>
  <dc:date>2006-11-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/296/Detecting-Spam-Blogs-A-Machine-Learning-Approach">
  <title><![CDATA[Detecting Spam Blogs: A Machine Learning Approach]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/296/Detecting-Spam-Blogs-A-Machine-Learning-Approach</link>
  <description><![CDATA[Weblogs or blogs are an important new way to publish
information, engage in discussions, and form communities
on the Internet. The Blogosphere has unfortunately
been infected by several varieties of spam-like
content. Blog search engines, for example, are inundated
by posts from splogs – false blogs with machine
generated or hijacked content whose sole purpose is to
host ads or raise the PageRank of target sites. We discuss
how SVM models based on local and link-based
features can ...]]></description>
  <dc:date>2006-07-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/299/Characterizing-the-Splogosphere">
  <title><![CDATA[Characterizing the Splogosphere]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/299/Characterizing-the-Splogosphere</link>
  <description><![CDATA[Weblogs or blogs collectively constitute the Blogosphere, forming
an influential and interesting subset on theWeb. As with
most Internet-enabled applications, the ease of content creation
and distribution makes the blogosphere spam prone.
Spam blogs or splogs are blogs hosting spam posts, created
using machine generated or hijacked content for the sole purpose
of hosting ads or raising the PageRank of target sites.
These splogs make up the splogosphere, and are now inundating
blog sea...]]></description>
  <dc:date>2006-05-23</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/269/SVMs-for-the-Blogosphere-Blog-Identification-and-Splog-Detection">
  <title><![CDATA[SVMs for the Blogosphere: Blog Identification and Splog Detection]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/269/SVMs-for-the-Blogosphere-Blog-Identification-and-Splog-Detection</link>
  <description><![CDATA[Weblogs, or blogs have become an important new way to publish
information, engage in discussions and form communities. The
increasing popularity of blogs has given rise to search and analysis
engines focusing on the 'blogosphere'.  A key requirement of such
systems is to identify blogs as they crawl the Web.
While this ensures that only blogs are indexed, blog search engines
are also often overwhelmed by spam blogs (splogs). Splogs not only
incur computational overheads but also reduce...]]></description>
  <dc:date>2006-03-27</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/227/On-Leveraging-Social-Media">
  <title><![CDATA[On Leveraging Social Media]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/227/On-Leveraging-Social-Media</link>
  <dc:date>2007-06-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/241/spam-in-blogs-and-social-media">
  <title><![CDATA[spam in blogs and social media]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/241/spam-in-blogs-and-social-media</link>
  <description><![CDATA[Spam on the Internet dates back over a decade, with its earliest known appearance as an email about the infamous MAKE.MONEY.FAST. campaign. Spam has co-evolved with Internet applications and is now quite common on the World-Wide Web.

As social media systems such as blogs, wikis and bookmark sharing sites have emerged, spammers have quickly developed techniques to infect them as well. The very characteristics underlying the Web, be it version 1.0, 2.0 or 3.0, also enable new varieties of sp...]]></description>
  <dc:date>2007-03-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/296/Adversarial-Classification-An-Ensemble-based-approach">
  <title><![CDATA[Adversarial Classification: An Ensemble-based approach]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/296/Adversarial-Classification-An-Ensemble-based-approach</link>
  <description><![CDATA[Master's Thesis Defense Announcement

Spam has been studied and dealt with extensively in the email, web, and, recently, blog domains. Recent work has addressed the problem of non-stationarity of the data using ensemble-based approaches. Adversarial classification has been handled by retraining base classifiers using labeled samples obtained from the ensemble. However, frequent retraining is expensive. There is a need is to dynamically determine when the classifiers should be retrained and ...]]></description>
  <dc:date>2009-04-27</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/212/Detecting-Spam-Blogs-An-Adaptive-Online-Approach-">
  <title><![CDATA[Detecting Spam Blogs: An Adaptive Online Approach]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/212/Detecting-Spam-Blogs-An-Adaptive-Online-Approach-</link>
  <description><![CDATA[Weblogs, or blogs, are an important new way to publish information, engage
in discussions, and form communities on the Internet. Blogs are a global
phenomenon, and with numbers well over 100 million they form the core of
the emerging paradigm of Social Media. While the utility of blogs is
unquestionable, a serious problem now afflicts them, that of spam. Spam
blogs, or splogs are blogs with auto-generated or plagiarized content
with the sole purpose of hosting profitable contextual ads ...]]></description>
  <dc:date>2007-09-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/213/Detecting-spam-blogs-beta-">
  <title><![CDATA[Detecting spam blogs (beta)]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/213/Detecting-spam-blogs-beta-</link>
  <description><![CDATA[In our regular weekly Ebiquity meeting, Pranam Kolari will give us a preview of his dissertation defense presentation.  He will greatly appreciate feedback on this pre-release beta version, as long as it doesn't involve suggestions that he do an additional six months of research to confirm and strengthen his experimental results.

See  his defense announcement for the abstract.]]></description>
  <dc:date>2007-09-24</dc:date>
 </item>
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