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User-Assisted Information Extraction from Twitter During Emergencies
Zoha Sheikh
Hira Masood
Sharifullah Khan
Muhammad Imran
Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds
Disasters and emergencies bring uncertain situations. People involved in such situations look for quick answers to their rapid queries. Moreover, humanitarian organizations look for situational awareness information to launch relief operations. Existing studies show the usefulness of social media content during crisis situations. However, despite advances in information retrieval and text processing techniques, access to relevant information on Twitter is still a challenging task. In this paper, we propose a novel approach to provide timely access to the relevant information on Twitter. Specifically, we employee Word2vec embeddings to expand initial users queries and based on a relevance feedback mechanism we retrieve relevant messages on Twitter in real-time. Initial experiments and user studies performed using a real world disaster dataset show the significance of the proposed approach.
openurl:?ctx_ver=Z39.88-2004&rfr_id=info%3Asid%2Fidl.iscram.org%2F&genre=proceeding&title=User-Assisted%20Information%20Extraction%20from%20Twitter%20During%20Emergencies&stitle=Iscram%202017&issn=2411-3387&date=2017&spage=684&epage=691&aulast=Zoha%20Sheikh&au=Hira%20Masood&au=Sharifullah%20Khan&au=Muhammad%20Imran&pub=Iscram&place=Albi%2C%20France&sid=refbase%3AISCRAM
url:http://idl.iscram.org/show.php?record=2056
citekey:ZohaSheikh_etal2017
citation:Zoha Sheikh, Hira Masood, Sharifullah Khan, & Muhammad Imran. (2017). User-Assisted Information Extraction from Twitter During Emergencies. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 684-691). Albi, France: Iscram.
2017
ConferencePaper
text
social media
disaster response
query expansion
supervised learning
file:http://idl.iscram.org/files/zohasheikh/2017/2056_ZohaSheikh_etal2017.pdf
Iscram
English
2411-3387
Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management
2017
684
691
1