Memory Remains: Understanding Collective Memory in the Digital Age
arXiv:1609.02621 · doi:10.1126/sciadv.1602368
Abstract
Recently developed information communication technologies, particularly the Internet, have affected how we, both as individuals and as a society, create, store, and recall information. Internet also provides us with a great opportunity to study memory using transactional large scale data, in a quantitative framework similar to the practice in statistical physics. In this project, we make use of online data by analysing viewership statistics of Wikipedia articles on aircraft crashes. We study the relation between recent events and past events and particularly focus on understanding memory triggering patterns. We devise a quantitative model that explains the flow of viewership from a current event to past events based on similarity in time, geography, topic, and the hyperlink structure of Wikipedia articles. We show that on average the secondary flow of attention to past events generated by such remembering processes is larger than the primary attention flow to the current event. We are the first to report these cascading effects.
Under Review
References in corpus (8)
- What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis
- Forecasting the 2013--2014 Influenza Season using Wikipedia
- Mining Missing Hyperlinks from Human Navigation Traces: A Case Study of Wikipedia
- Improving Website Hyperlink Structure Using Server Logs
- Wikipedia traffic data and electoral prediction: towards theoretically informed models
- Wikipedia Page View Reflects Web Search Trend
- Emergent user behavior on Twitter modelled by a stochastic differential equation
- Dynamics and Biases of Online Attention: The Case of Aircraft Crashes