One of the major trends at the 35th annual European Conference on Information Retrieval was event related data. The conference took place between the 24th and 27th of March this year in a snowy Moscow, Russia. It attracted around 300 participants from all over the globe, 3 of them findwizards. While ECIR 2013 provided talks on a large variety of topics from across the field, event related data was definitely a buzz word.
The keynote speaker opening the second day of conference was Rutgers University assistant professor and Mahaya inc. CTO Mor Naaman. In his talk, Mr Naaman let the following image explain why Mahaya inc. are in business.
The past two papal elections.
The image above clearly shows that the way people act at events has changed considerably in the past few years, nowadays everyone is a reporter and their stories can be found on social media. Using platforms such as Twitter, Facebook and YouTube as data sources Naaman’s company creates products which not only extracts, but also synchronizes event coverage. One interesting feature in their latest product is the synchronization of video clips, making it possible for a user to easily switch view when watching video footage of for example a concert. An arguably even stronger feature of this use of social media is the fact that news and event footage can reach the world even if no press is present at the scene. Slides from this inspiring talk can be found here.
Another presentation the same day displayed promising results in the task of automatic event detection. Using machine learning algorithms a team of researchers from Hanover, Germany have designed a system for detecting and summarizing entity related events from Wikipedia edit history data. Basically the idea is that when a Wikipedia article is edited by a large amount of users in a short period of time that can mark an important event considering the subject of the article. More information about this research can be found here.
The last day of the conference opened with a presentation from Jimmy Lin of Twitter. His talk centered on the importance of fast real-time indexing in social media platform architecture. One of the strengths of Twitter is presenting the users with information about events as they happen. As an example of this he used the event of an earthquake hitting eastern USA in 2011. Tweets from locations closer to the epicenter of the earthquake reached Twitter users in New York City before the actual quake did. I have to admit “Twitter, faster than earthquakes” is a pretty good slogan.
So whether it’s using social media data to let people (re)visit events, automatic event detection in open source dictionaries, making sure your indexing is fast enough to let your users cover events as they happen or something else, event based data seems to be one of the driving forces in the field of IR at the moment.