IIIT-Delhi Institutional Repository

Me, myself and my killfie: characterizing and preventing selfie deaths

Show simple item record

dc.contributor.author Vachher, Mayank
dc.contributor.author Kumaraguru, Ponnurangam (Advisor)
dc.date.accessioned 2017-11-13T11:33:41Z
dc.date.available 2017-11-13T11:33:41Z
dc.date.issued 2016-11-16
dc.identifier.uri http://repository.iiitd.edu.in/xmlui/handle/123456789/569
dc.description.abstract Over the past couple of years, clicking and posting selfies has become a popular trend. However, since March 2014, 127 people have died and many have been injured while trying to click a selfie. Researchers have studied selfies for understanding the psychology of the authors, and understanding its effect on social media platforms. In this work, we perform a comprehensive analysis of the selfie-related casualties and infer various reasons behind these deaths. We use inferences from incidents and from our understanding of the features, we create a system to make people more aware of the dangerous situations in which these selfies are taken. We use a combination of text-based, image-based and location-based features to classify a particular selfie as dangerous or not. Our method ran on 3,155 annotated selfies collected on Twitter gave 73% accuracy. Individually the image-based features were the most informative for the prediction task. The combination of image-based and location-based features resulted in the best accuracy. We have made our dataset available at http://labs.precog.iiitd.edu.in/killfie. en_US
dc.language.iso en_US en_US
dc.subject Machine learning en_US
dc.subject Information retrieval en_US
dc.subject Social computing en_US
dc.title Me, myself and my killfie: characterizing and preventing selfie deaths en_US
dc.type Other en_US

Files in this item

This item appears in the following Collection(s)

Show simple item record

Search Repository

Advanced Search


My Account