@article{ieeesandp2017,
 abstract = {A novel machine-based classifier system leverages Twitter user anonymity patterns and their correlation to content sensitivity to automatically identify accounts that tweet sensitive content. Anonymity's role in society and the nuances and complexity of content sensitivity are confirmed.},
 author = {Peddinti, Sai Teja and Ross, Keith W. and Cappos, Justin},
 doi = {10.1109/MSP.2017.74},
 journal = {IEEE Security & Privacy},
 keywords = {Twitter;Privacy;Computer security;Uniform resource locators;Labeling;Social network services;Sensitivity;privacy;Twitter;social networks;social media;anonymity;anonymous;pseudonymous;real-name policy;content sensitivity},
 number = {3},
 pages = {84-87},
 title = {User Anonymity on Twitter},
 volume = {15},
 year = {2017}
}