Computational Methods for Next-Generation Online Media Ecosystems

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Computational Methods for Next-Generation Online Media Ecosystems University of California Santa Barbara Computational Methods for Next-Generation Online Media Ecosystems A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science by May E. ElSherif Committee in charge: Professor Elizabeth Belding, Chair Professor William Wang Professor Amr Elabaddi December 2019 The Dissertation of May E. ElSherif is approved. Professor William Wang Professor Amr Elabaddi Professor Elizabeth Belding, Committee Chair August 2019 Computational Methods for Next-Generation Online Media Ecosystems Copyright c 2019 by May E. ElSherif iii In Memory of all Lives Lost due to Hate and Bigotry iv Acknowledgements This thesis is about responsibility to promote the good and prevent the harm. This work is the result of the best and most challenging years of my life. I would like to start by thanking my family who always put education at the forefront of their priorities. I am really grateful for all their efforts, their endless support, and love throughout my life. They taught me work ethic, perseverance, and ambition by example. To my dad, thank you for your generosity in providing me with whatever I needed through my education journey. To my mum, thank you for lending me an ear, being there whenever I needed you, and believing in me against all the odds. To my sister, thank you for giving me positive vibes and listening to all my stories. To my brother, who is not here today, you will always be in my thoughts and I wish you were here today. I cannot thank enough my research adviser, Elizabeth Belding. I have been fortunate to have her as my mentor, supporter, and my advocate. Not only did she believe in me as a researcher but also research line I chose to tackle. She always finds way to make research more interesting and impactful. I did not only learn how to be a good researcher from her but I also learned how to be a good mentor. I would not have been the researcher I am now if it weren't for her. Many thanks to my mentor William Wang who introduced me to the field of Natural Language Processing and how to tie it to problems with social impact. I had the great privilege to learn a lot from his vast knowledge and applying this knowledge in my work. To Amr Elabaddi, thank you for your insightful research questions and for always having an open door and open mind when I needed help. He always made me feel that I have a part of my Egyptian family away from home. To my collaborators: Mogran Vigil-Hayes, Ramya Raghavendra, Shirin Nilizadeh, Vivek Kulkarni, and Jing Qian, thank you for contributing to this work in many ways v and it was a joy to work with you. I had the privilege to work with and mentor many undergraduates who developed a passion for Computer Science research: Dana Nguyen, Xuewen Sherry Li, Barbara Korycki, Andrew Gaut, Tony Sun, Shirlyn Tan, and Yuxin Huang. Together, we engaged in tackling research problems and I enjoyed every discussion we had. Special thanks to Elizabeth Belding, William Wang, and Diba Mirza who guided me through the mentoring process and provided feedback whenever needed. I would like to especially thank Dana Nguyen who has demonstrated unprecedented excitement and dedication to research. We co-authored together multiple publications through which she showed persistence, ownership, and hard work. To my colleagues and friends: Morgan Vigil-Hayes, Victor Zakhary, Mohamed Wahba, Radwa Hamed, Nadah Feteih, Mahmoud Ramadan, Mai Said, Vivek Adarsh, and Esther Showalter. Your words of encouragement and our conversations kept me going through lots of challenges. Finally, I would like to specifically thank Mohamed Wahba for his support during lots of deadlines. He heard all my ideas, confusions, helped me practice so many talks, and constantly affirmed my place in the academic community. vi Curriculum Vitæ May E. ElSherif Education 2014-2019 Ph.D. in Computer Science, University of California, Santa Barbara. Advisor: Elizabeth Belding Thesis: Computational Methods for Next-Generation Online Media Ecosystems 2011-2013 M.Sc. in Wireless Communications and Information Technology, Nile University, Giza, Egypt. Advisors: Tamer ElBatt, Ahmed Zahran and Ahmed Helmy Thesis: Similarity Metrics and an Information-theoretic Framework for Opportunistic Mobile Social Networks 2006-2011 B.Sc. in Computer Engineering, Cairo University, Giza, Egypt. Graduated with Distinction Advisor: Hatem ElBoghdady Thesis: The Golden Retriever: A Robotic Odor Source Localizer Research Interests Social computing, natural language processing, data science, applied machine learning, computer-supported cooperative work, computational social science Awards & Honors 2019 UCSB Computer Science Outstanding Graduate Student Award 2018 UCSB Grad Slam Finalist (Public Speaking) 2017 UCSB Fiona and Michael Goodchild Graduate Mentoring Award 2011 Google Research Award (Nile University) 2011 Nile University Research Fellowship (Full academic scholarship) 2009 IEEE Best Project Award (Cairo University Student Brach) 2009 Ideal Student Award (Cairo University) 2008 Best Volunteer Team (Suzanne Mubarak Women's International Peace Movement NGO) Publications Refereed Papers [1] J. Qian, M. ElSherief, E. Belding, and W. Yang Wang. Learning to Decipher Hate Symbols. In North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT'19). vii [2] A. Gaut, T. Sun, S. Tang, Y. Huang, M. ElSherief, J. Zhao, D. Mirza, E. Belding, K. Chang, and W. Yang Wang. Mitigating Gender Bias in Natural Language Processing: Literature Review. In Annual Meeting of the Association for Computational Linguistics (ACL'19), 2019. [3] J. Qian, M. ElSherief, E. Belding, and W. Yang Wang. Hierarchical CVAE for Fine- Grained Hate Speech Classification. In Empirical Methods of Natural Language Process- ing (EMNLP'18), November 2018. [25% Acceptance Rate]. [4] J. Qian, M. ElSherief, E. Belding, and W. Yang Wang. Leveraging Intra-User and Inter-User Representation Learning for Automated Hate Speech Detection. In North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT'18), June 2018. [18% Acceptance Rate]. [5] M. ElSherief, V. Kulranki, D. Nguyen, W. Yang Wang, and E. Belding. Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media. In AAAI Conference on Web and Social Media (ICWSM'18), June 2018. [16% Acceptance Rate]. [6] M. ElSherief, S. Nilizadeh, D. Nguyen, G. Vigna, and E. Belding. Peer to Peer Hate: Hate Speech Instigators and Their Targets. In AAAI Conference on Web and Social Media (ICWSM'18), June 2018. [16% Acceptance Rate]. [7] M. ElSherief, B. Alipour, M. Al Qathrady, T. ElBatt, A. Zahran, and A. Helmy. A Novel Mathematical Framework for Similarity-based Opportunistic Social Networks. Elsevier Pervasive and Mobile Computing, 42:134{150, December 2017. [Journal Exten- sion]. [8] M. ElSherief, M. Vigil-Hayes, R. Raghavendra, and E. Belding. Whom to Query? Spatially-Blind Participatory Crowdsensing under Budget Constraints. In ACM Work- shop on Mobile Crowdsensing Systems and Applications (CrowdSenSys'17), November 2017. [9] M. ElSherief, E. Belding, and D. Nguyen. #NotOkay: Understanding Gender-based Violence in Social Media. In AAAI Conference on Web and Social Media (ICWSM'17), May 2017. [14% Acceptance Rate]. [10] M. ElSherief, T. ElBatt, A. Zahran, and A. Helmy. An Information-theoretic Model for Knowledge Sharing in Opportunistic Social Networks. In IEEE Conference on Social Computing and Networking (SocialCom'15), December 2015. [25% Acceptance Rate]. [11] M. ElSherief and E. Belding. The Urban Characteristics of Street Harassment: A First Look. In ACM Workshop on Smart Cities and Urban Analytics (UrbanGIS'15), November 2015. [12] M. ElSherief, T. ElBatt, A. Zahran, and A. Helmy. The Quest for User Similarity in Mobile Societies. In IEEE Workshop on Social and Community Intelligence (SCI'14), March 2014. [17% Acceptance Rate]. viii Other Contributions [13] M. ElSherief. Compressed Lexicon and Currently the Largest Twitter Hate Speech Dataset. https://github.com/mayelsherif/hate_speech_icwsm18, June 2018. [14] M. ElSherief, M. Vigil-Hayes, R. Raghavendra, and E. Belding. Whom to Query? Spatially-Blind Participatory Crowdsensing under Budget Constraints. In AAAI Confer- ence on Human Computation and Crowdsourcing (HCOMP'17), October 2017. [Poster]. [15] M. ElSherief, T. ElBatt, A. Zahran, and A. Helmy. O'BTW: An Opportunistic Similarity-based Mobile Recommendation System. In ACM Conference on Mobile Sys- tems, Applications and Services (MobiSys'13), June 2013. [Demo]. Experience CS8: Introduction to Computer Science, Instructor of Record, UCSB. [Summer 2019] UCSB MOMENT Lab, Gradaute Research Assistant, Santa Barbara, CA. [2014-2019] Early Research Scholars Program (ERSP), Lead TA, UCSB. [Fall 2018-Spring 2019] Berkman Klein Center for Internet and Society (BKC), Harvard University, Research Intern, Cambridge, MA. [Summer 2018] Polaris Wireless Research, Data Science Intern, Mountain View, CA. [Summer 2016] Wireless Intelligent Networks Center, Research Assistant, Nile University, Giza, Egypt. [2011-2013] Center of Informatics Science, Bioinformatics Intern, Nile University, Giza, Egypt. [Summer 2010] Teaching Assistant, Computer Science Department, UCSB. [Winter-Spring 2014] Teaching Assistant, Engineering Math and Physics Department, Cairo University. [2012-2013] ix Abstract Computational Methods for Next-Generation Online Media Ecosystems by May E. ElSherif Human biases
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