Towards reliable and responsible social network research by Tristan Henderson – University of St Andrews

Event details

  • When: 11th February 2013 15:00 - 16:00
  • Where: Phys Theatre C
  • Series: CS Colloquia Series
  • Format: Colloquium, Seminar

This seminar is suitable for CS3053-RPIC

Social network sites (SNSs) such as Facebook and Twitter are used by hundreds of millions of people daily. As such they represent an attractive source of data for research. Many researchers have crawled these SNSs to collect data for projects involving psychology, sociology, health, and of course computer science. But there are many risks to naively crawling an SNS, ranging from data protection and privacy concerns to the reliability of the collected data.

This talk will discuss various work that we have conducted to explore how we can conduct more reliable and responsible social network research. First, we present an experience sampling method user study which investigated location-sharing privacy; data which are impossible to collect by merely crawling an SNS. Second, we discuss the results of replicating two large SNS studies to explore informed consent and participant sharing preferences. Finally, we will discuss some new and outstanding challenges in data sharing and anonymisation that we have not even begun to tackle yet.

Tristan Henderson is a Senior Lecturer in Computer Science at the University of St Andrews. His research aims to better understand user behaviour and use this to build improved systems; an approach which has involved measurements and testbeds for networked games, wireless networks, mobile sensors, smartphones, and most recently online social
networks and opportunistic networks. He serves on the JANET UK Wireless Advisory Group, the steering committee of the ExtremeCom, HotPlanet and NetGames workshops, and is co-PI of the CRAWDAD data archive, the world’s largest wireless network data archive, with over 90 datasets and tools in use by over 4500 users from 90 countries. Dr
Henderson holds an MA in Economics from Cambridge and an MSc and PhD in Computer Science from UCL.
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