Event-based trend factor analysis based on hashtag correlation and temporal information mining Lee, Heng, Abdar, Moloud and Yen, Neil Y. 2018, Event-based trend factor analysis based on hashtag correlation and temporal information mining, Applied Soft Computing, vol. 71, pp. 1204-1215, doi: 10.1016/j.asoc.2018.02.044. Attached Files Name Description MIMEType Size Downloads Title Event-based trend factor analysis based on hashtag correlation and temporal information mining Author(s) Lee, Heng Abdar, Moloud orcid.org/0000-0002-3059-6357 Yen, Neil Y. Journal name Applied Soft Computing Volume number 71 Start page 1204 End page 1215 Total pages 12 Publisher Elsevier Place of publication Amsterdam, The Netherlands Publication date 2018-10 ISSN 1568-4946 Keyword(s) Event-based analysis Twitter Sentiment analysis Trend forecasting Social networks Language eng DOI 10.1016/j.asoc.2018.02.044 Indigenous content off Field of Research 0102 Applied Mathematics 0801 Artificial Intelligence and Image Processing 0806 Information Systems HERDC Research category C1 Refereed article in a scholarly journal Persistent URL http://hdl.handle.net/10536/DRO/DU:30134222 Document type: Journal Article Collections: Training - Quality check Deputy Vice-Chancellor Research Group Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Thu, 30 Jan 2020, 14:30:38 EST Fri, 31 Jan 2020, 04:00:27 EST Fri, 31 Jan 2020, 07:09:33 EST Tue, 14 Jul 2020, 06:02:27 EST Wed, 29 Jul 2020, 10:09:56 EST Wed, 29 Jul 2020, 10:19:13 EST Wed, 29 Jul 2020, 10:19:50 EST Filtered Full Citation counts:   Cited 2 times in TR Web of Science Cited 4 times in Scopus Search Google Scholar Access Statistics: 19 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Thu, 30 Jan 2020, 14:30:38 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.