Original paper
Private traits and attributes are predictable from digital records of human behavior
Volume: 110, Issue: 15, Pages: 5802 - 5805
Published: Mar 11, 2013
Abstract
We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided...
Figures & Tables
Fig. 1. The study is basedona sampleof 58,466volunteers fromtheUnited States, ob...
Fig. 2. Prediction accuracy of classification for dichotomous/dichotomized attri...
Fig. 3. Prediction accuracy of regression for numeric attributes and traits expr...
Fig. 4. Accuracy of selected predictions as a function of the number of availabl...
Paper Details
Title
Private traits and attributes are predictable from digital records of human behavior
Published Date
Mar 11, 2013
Volume
110
Issue
15
Pages
5802 - 5805
TrendsPro
You’ll need to upgrade your plan to Pro
Looking to understand a paper’s academic impact over time?
- Scinapse’s Citation Trends graph enables the impact assessment of papers in adjacent fields.
- Assess paper quality within the same journal or volume, irrespective of the year or field, and track the changes in the attention a paper received over time.
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.