Proceedings:
Vol. 10 No. 1 (2016): Tenth International AAAI Conference on Web and Social Media
Volume
Issue:
Vol. 10 No. 1 (2016): Tenth International AAAI Conference on Web and Social Media
Track:
Poster Papers
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Abstract:
We explore the feasibility of automatically finding accounts that publish sensitive content on Twitter, by examining the percentage of anonymous and identifiable followers the accounts have. We first designed a machine learning classifier to automatically determine if a Twitter account is anonymous or identifiable. We then classified an account as potentially sensitive based on the percentages of anonymous and identifiable followers the account has. We applied our approach to approximately 100,000 accounts with 404 million active followers. The approach uncovered accounts that were sensitive for a diverse number of reasons.
DOI:
10.1609/icwsm.v10i1.14782
ICWSM
Vol. 10 No. 1 (2016): Tenth International AAAI Conference on Web and Social Media