{"type":"ScholarlyArticle","title":"Using Social Media to Enhance Emergency Situation Awareness: Extended Abstract","authors":[{"name":"Jie Yin","slug":"jie-yin","given":"Jie","family":"Yin","affiliation":""},{"name":"Sarvnaz Karimi","slug":"sarvnaz-karimi","given":"Sarvnaz","family":"Karimi","affiliation":""},{"name":"Andrew Lampert","slug":"andrew-lampert","given":"Andrew","family":"Lampert","affiliation":""},{"name":"Mark A. Cameron","slug":"mark-a-cameron","given":"Mark A.","family":"Cameron","affiliation":""},{"name":"Bella Robinson","slug":"bella-robinson","given":"Bella","family":"Robinson","affiliation":""},{"name":"Robert Power","slug":"robert-power","given":"Robert","family":"Power","affiliation":""}],"abstract":"Social media platforms, such as Twitter, offer a rich source of real-time information about real-world events, particularly during mass emergencies. Sifting valuable information from social media provides useful insight into time-critical situations for emergency officers to understand the impact of hazards and act on emergency responses in a timely manner. This work focuses on analyzing Twitter messages generated during natural disasters, and shows how natural language processing and data mining techniques can be utilized to extract situation awareness information from Twitter. We present key relevant approaches that we have investigated including burst detection, tweet filtering and classification, online clustering, and geotagging.","doi":null,"url":"https://ijcai.org/proceedings/2015/602","pdf":"https://ijcai.org/proceedings/2015/0602.pdf","markdown":"https://ijcai.org/proceedings/2015/602.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/602","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Journal Track","track":"Journal Track","number":602,"pages":{"first":4234,"last":4238},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}