Our work on detecting person locations in social media has been accepted for presentation at the 10th ACM Conference on Web Science, which will be held in Amsterdam, Netherlands, on 27-30 May 2018. The paper is titled "Where in the World Is Carmen Sandiego? Detecting Person Locations via Social Media Discussions", by Konstantina Lazaridou, Toni Gruetze and Felix Naumann.
Abstract:
In today’s social media, news often spread faster than in mainstream media outlets, along with additional context and aspects about the current affairs. Consequently, users in social networks are up-to-date with the details of real-world events and the involved individuals. Examples include crime scenes and potential perpetrator descriptions, public gatherings with rumors about celebrities among the guests, rallies by prominent politicians, concerts by musicians, etc. We are interested in the problem of tracking persons mentioned in social media, namely detecting the locations of individuals by leveraging the discussions about them. Existing literature focuses on the well-known and more convenient problem of user location detection in social media, mainly as the location discovery of the user profiles and their messages. In contrast, we track individuals with text mining techniques, regardless whether they hold a social network account or not. We observe what the community shares about them and estimate their locations. Our approach consists of two steps: firstly, we introduce a noise filter that prunes irrelevant posts using a recursive partitioning technique. Secondly, we built a model that reasons over the set of messages regarding an individual and determines his/her locations. In our experiments, we successfully trace the last U.S. presidential candidates through millions tweets published from November 2015 until January 2017. Our results outperform previously introduced techniques and various baselines.
