Dr Taha Yasseri
Former Senior Research Fellow
Project role: Principal Investigator
Taha Yasseri analyses large-scale transactional data to understand human dynamics, collective behaviour, collective intelligence and machine intelligence.
Memory and the way we remember, forget, and recall events, people, places, and so on, have been a very sophisticated topic of theoretical research for a long time (Ebbinghaus-1885). The notion of collective memory as a socially generated common perception of an item has only recently been introduced and studied (Halbwachs-1992), around the time our societies started to become highly connected through new channels of communication. However, these studies are all concerned with offline settings, whilst the developments in digital technologies in recent years have influenced the way that we keep track of events both at individual and collective levels significantly. These technologies have also provided us with huge amounts of data, which are being used to study different aspects of our social behaviour.
There have only been a few large scale empirical studies on online remembering at the global level using these data. Work by Au Yeung and Adam Jatowt (2011) analysed references to the past in large news collections, but this only considered the memory with a journalistic bias and limited to only mentions of specific dates. This project will study remembering based on the information seeking patterns of large number of individuals on the web, by using Google search logs and temporal analysis on the search volumes constructed from Google Trends and Google Correlate. Although information seeking is not equivalent to memory, we argue that it is a reliable indicator of memory, or at least one needs to have a recollection of an item to want to perform a web search on it.
This project impacts a wide range of audiences and practices. Many questions and concerns about the way search engines work, or should work, can be tackled empirically by using the data that are produced on those platforms themselves. We will investigate whether, our memory and remembering pattern has a complex non-trivial and high pace dynamic, even if these new technologies theoretically make it impossible to forget at the individual level, as it has been claimed. The outcomes of the project can play an important role in informing and shaping the currently under-developed policies at the EU level and elsewhere. Additionally, our results could have applications in marketing, online opinion polling, broadcasting strategy, and forecasting and nowcasting of social collective behaviours.
Ebbinghaus, Hermann. Über das gedächtnis: untersuchungen zur experimentellen psychologie. Duncker & Humblot, 1885.
Halbwachs, Maurice. On collective memory. University of Chicago Press, 1992.
Au Yeung, Ching-man, and Adam Jatowt. “Studying how the past is remembered: towards computational history through large scale text mining.” Proceedings of the 20th ACM international conference on Information and knowledge management. ACM, 2011.
Mayer-Schönberger, Viktor. Delete: the virtue of forgetting in the digital age. Princeton University Press, 2011.
Former Senior Research Fellow
Project role: Principal Investigator
Taha Yasseri analyses large-scale transactional data to understand human dynamics, collective behaviour, collective intelligence and machine intelligence.
Former
Ruth García Gavilanes is a Postdoctoral researcher and data scientist at the OII.
Former
Milena Tsvetkova is a sociologist who uses computational and online technologies to study fundamental social phenomena such as cooperation, contagion, and inequality.
The Guardian, 12 October 2016
Researchers at the Oxford Internet Institute examine Wikipedia articles about some 1,500 crashes around the world.
Science, 11 October 2016
OII researchers find that when a crash involves fewer than 50 deaths, Wikipedia readers tended to pay relatively little attention.
MIT Technology Review, 07 July 2016
Traffic to Wikipedia pages about aircraft crashes varies in unexpected ways, say Ruth García-Gavilanes, Milena Tsvetkova, and Taha Yasseri.