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	<pub:InProceedings rdf:about="http://ebiquity.umbc.edu/paper/html/id/623/Faking-Sandy-Characterizing-and-Identifying-Fake-Images-on-Twitter-during-Hurricane-Sandy">
		<rdfs:label><![CDATA[Faking Sandy: Characterizing and Identifying Fake Images on Twitter during Hurricane Sandy]]></rdfs:label>
		<pub:title><![CDATA[Faking Sandy: Characterizing and Identifying Fake Images on Twitter during Hurricane Sandy]]></pub:title>
		<pub:publishedOn rdf:datatype="&xsd;dateTime">2013-05-13T00:00:00-05:00</pub:publishedOn>
		<pub:abstract><![CDATA[In today’s world, online social media plays a vital role during real world events, especially crisis events. There are both positive and negative eﬀects of social media coverage of events -- it can be used by authorities for eﬀective disaster management or by malicious entities to spread rumors and fake news. The aim of this paper is to highlight the role of Twitter during Hurricane Sandy (2012) to spread fake images about the disaster. We identiﬁed 10,350 unique tweets containing fake images that were circulated on Twitter during Hurricane Sandy. We performed a characterization analysis, to understand the temporal, social reputation and inﬂuence patterns for the spread of fake images. Eighty six percent of tweets spreading the fake images were retweets, hence very few were original tweets. Our results showed that top thirty users out of 10,215 users (0.3%) resulted in 90% of the retweets of fake images; also network links, such as follower relationships of Twitter, contributed very less (only 11%) to the spread of these fake photos URLs. Next, we used classiﬁcation models to distinguish fake images from real images of Hurricane Sandy. Best results were obtained from Decision Tree classiﬁer from which we got 97% accuracy in predicting fake images from real. Also, tweet based features were very eﬀective in distinguishing fake images tweets from real, while the performance of user based features was very poor. Our results showed that automated techniques can be used in identifying real images from fake images posted on Twitter.]]></pub:abstract>
		<pub:note><![CDATA[(held in conjunction with the 22th International World Wide Web Conference)]]></pub:note>
		<pub:counter>4441</pub:counter>
		<pub:tag><![CDATA[social media]]></pub:tag>
		<pub:booktitle><![CDATA[Second International Workshop on Privacy and Security in Online Social Media (PSOSM)]]></pub:booktitle>
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					<person:Person rdf:about="http://ebiquity.umbc.edu/person/html/Anupam/Joshi"><person:name><![CDATA[Anupam Joshi]]></person:name><rdfs:label><![CDATA[Anupam Joshi]]></rdfs:label></person:Person>
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							<person:Person rdf:about="http://ebiquity.umbc.edu/person/html/Ponnurangam/Kumaraguru"><person:name><![CDATA[Ponnurangam Kumaraguru]]></person:name><rdfs:label><![CDATA[Ponnurangam Kumaraguru]]></rdfs:label></person:Person>
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									<person:Person rdf:about="http://ebiquity.umbc.edu/person/html/Hemank/Lamba"><person:name><![CDATA[Hemank Lamba]]></person:name><rdfs:label><![CDATA[Hemank Lamba]]></rdfs:label></person:Person>
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<person:Person rdf:about="http://ebiquity.umbc.edu/person/html/Anupam/Joshi"><person:name><![CDATA[Anupam Joshi]]></person:name><rdfs:label><![CDATA[Anupam Joshi]]></rdfs:label></person:Person>
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			<pub:softCopyFormat><![CDATA[PDF Document]]></pub:softCopyFormat>
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