Loose tweets: an analysis of privacy leaks on twitter

By Huina Mao, Xin Shuai, Apu Kapadia. 2011

214 citations recorded by the source corpus.

Twitter has become one of the most popular microblogging sites for people to broadcast (or "tweet") their thoughts to the world in 140 characters or less. Since these messages are available for public consumption, one may expect these tweets not to contain private or incriminating information. Nevertheless we observe a large number of users who unwittingly post sensitive information about themselves and other people for whom there may be negative consequences. While some awareness exists of such privacy issues on social networks such as Twitter and Facebook, there has been no quantitative, scientific study addressing this problem. In this paper we make three major contributions. First, we characterize the nature of privacy leaks on Twitter to gain an understanding of what types of private information people are revealing on it. We specifically analyze three types of leaks: divulging vacation plans, tweeting under the influence of alcohol, and revealing medical conditions. Second, using this characterization we build automatic classifiers to detect incriminating tweets for these three topics in real time in order to demonstrate the real threat posed to users by, e.g., burglars and law enforcement. Third, we characterize who leaks information and how. We study both self- incriminating primary leaks and secondary leaks that reveal sensitive information about others, as well as the prevalence of leaks in status updates and conversation tweets. We also conduct a cross-cultural study to investigate the prevalence of leaks in tweets originating from the United States, United Kingdom and Singapore. Finally, we discuss how our classification system can be used as a defense mechanism to alert users of potential privacy leaks.

Subfields: Information Systems, Sociology and Political Science, Safety, Robustness & Interpretability, Privacy & Security

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

In Sociology and Political Science

In Safety, Robustness & Interpretability

In Privacy & Security

Citations in the corpus

Ethical and social risks of harm from Language Models (2021, background): “…through no fault of the affected individual, e.g. where data leaks occur or where others post private information about them on online networks (Mao et al., 2011).8 Disclosure of private information can have the same effects as doxing9, namely causing psychological and material harm (Douglas,…”
“Participant” Perceptions of Twitter Research Ethics (2018, background): “Privacy is also an issue on Twitter due to accidental information leaks by users, such as divulging vacation plans, tweeting under the influence, or revealing medical conditions (Mao, Shuai, & Kapadia, 2011).”
The Tweets They Are a-Changin: Evolution of Twitter Users and Behavior (2014, background): “Yang et al. 2012)), to examining how privacy leaks and violations can occur (Mao, Shuai, and Kapadia 2011; Meeder et al. 2010), and even using aggregated data from Twitter to predict the behavior of real-world phenomena such as the stock market (Gilbert and Karahalios 2010).”
Geolocation Prediction in Social Media Data by Finding Location Indicative Words (2012, background): “While acknowledging potential privacy concerns (Mao et al., 2011; Pontes et al., 2012), accurate user geolocation is a key driver for location-speciﬁc services such as localised search, and has been the target of research across different disciplines.”
From "I Love You Babe" to "Leave Me Alone" - Romantic Relationship Breakups on Twitter (2014, background): “Interestingly, though there is work on privacy issues on Twitter [18,26], we are not aware of any study that looks at when and why users change their Twitter privacy settings.”