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Understanding Site-Based Inference Potential for Identifying Hidden Attributes.

, , , , , and . SocialCom, page 570-577. IEEE Computer Society, (2013)

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Using Network Flows to Identify Users Sharing Extremist Content on Social Media., and . PAKDD (1), volume 10234 of Lecture Notes in Computer Science, page 330-342. (2017)Identification of extremism on Twitter., , and . ASONAM, page 1251-1255. IEEE Computer Society, (2016)Helping Users Understand Their Web Footprints., , , , , , , , , and . WWW (Companion Volume), page 117-118. ACM, (2015)Understanding the impact of sampling and noise on detecting events using twitter., and . IEEE BigData, page 4855-4857. IEEE Computer Society, (2017)Detecting and Using Buzz from Newspapers to Understand Patterns of Movement., , , , and . IEEE BigData, page 5336-5338. IEEE, (2018)Overlapping Target Event and Story Line Detection of Online Newspaper Articles., , , and . DSAA, page 222-232. IEEE, (2016)A framework for detecting public health trends with Twitter., , , , and . ASONAM, page 556-563. ACM, (2013)Understanding Site-Based Inference Potential for Identifying Hidden Attributes., , , , , and . SocialCom, page 570-577. IEEE Computer Society, (2013)Cancer subtyping with heterogeneous multi-omics data via hierarchical multi-kernel learning., , , , , , and . Briefings Bioinform., (January 2023)Understanding evolving group structures in time-varying networks., , , , and . ASONAM, page 142-148. ACM, (2013)