Social Media Analytics: Digital Footprints


Monday, April 15, 2013, 10:30am - Monday, April 15, 2013, 11:30am

325b ITE, UMBC

social media, twitter

Social media has greatly impacted the way we communicate today. With approximately 3000 tweets/sec and 55 million FB status updates a day, it is a great way to disseminate information to users across the world. However such a tool can also be used to disseminate misinformation in a quick and efficient manner which can have a harmful impact in multiple scenarios like national security cases, or business/marketing cases and hence needs to be curbed and kept in check. Our approach involves creating a social footprint of users, which can be used to distinguish real and imposter/ compromised accounts on social media.

In this work, we build the signature or the profile of users claiming to be the same entity on the social media – beginning with "famous" personalities (Here we assume that spreading malicious content through such “famous accounts” would have more impact and thus a higher threat). This signature is built based on content and network analysis of such users on social media. We analyze the real time content of users (tweets/Facebook posts etc.) and compare the same with information about the user from reliable sources on the web (news papers / news channels etc.), in order to compute a similarity metric between content from the two sources. We also compute a metric based on the social network analysis of the users. Once the validity of such an user account is established based on the two above metrics, we filter down this user’s social media network and apply the same technique to authenticate less famous people's (layman's) user accounts.

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