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========================================== SOFTWARE LICENSE AGREEMENT - ArSenTD-Lev ========================================== * NAME: ArSenTD-Lev : Arabic Sentiment Twitter Dataset for LEVantine dialect * LICENSE This software and database is being provided to you, the LICENSEE, by the Owners under the following license. By obtaining, using and/or copying this software and database, you agree that you have read, understood, and will comply with these terms and conditions. You further agree that you have read and you will abide by the license agreements provided in the above links under “acknowledgements”: Permission to use, copy, modify and distribute this software and database and its documentation for any purpose and without fee or royalty is hereby granted, provided that you agree to comply with the following copyright notice and statements, including the disclaimer, and that the same appear on ALL copies of the software, database and documentation, including modifications that you make for internal use or for distribution. [ArSenTD-Lev ] Copyright 2018 by [American University of Beirut]. All rights reserved. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as this one. You may not apply legal terms or technological measures that legally restrict others from doing anything this license permits. THIS SOFTWARE IS PROVIDED "AS IS" AND THE OWNERS MAKE NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, THE OWNERS MAKE NO REPRESENTATIONS OR WARRANTIES OF MERCHANT-ABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF THE LICENSED SOFTWARE, DATABASE OR DOCUMENTATION WILL NOT INFRINGE ANY THIRD PARTY PATENTS, COPYRIGHTS, TRADEMARKS OR OTHER RIGHTS. The name of the Owners may not be used in advertising or publicity pertaining to distribution of the software and/or database. Title to copyright in this software, database and any associated documentation shall at all times remain with the Owners and LICENSEE agrees to preserve same. The use of ArSenTD-Lev should be cited as follows: @article{ArSenTDLev2018, title={ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets}, author={Baly, Ramy, and Khaddaj, Alaa and Hajj, Hazem and El-Hajj, Wassim and Bashir Shaban, Khaled}, journal={OSACT3}, pages={}, year={2018} [ArSenTD-Lev] Copyright 2018 by [American University of Beirut]. All rights reserved. ==========================================

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