Emaad
Manzoor

I am a PhD candidate in the Heinz College at Carnegie Mellon University. I design randomized experiments and quasi-experimental studies to quantify the persuasive power of mental shortcuts in text-based communication, and how language and rhetoric can be used to moderate this power. I also develop data-mining techniques for evolving networks and statistical frameworks for causal inference with text. I am advised by Dokyun Lee and George Chen, and my research is supported by a McKinsey & Company Ph.D. Fellowship.

I will join the University of Wisconsin-Madison as an Assistant Professor of Operations and Information Management in August 2021.

Recent News

• 2020.12: Selected to the inaugral cohort of Rising Stars in Data Science by the Center for Data and Computing at the University of Chicago!
• 2020.12: Paper on linguistic biases in peer review with Nihar B. Shah accepted to the AAAI 2021 main conference!
• 2020.12: Paper on influence via ethos accepted to the AAAI 2021 workshop on AI for Behavioral Change!
• 2020.11: Proposed workshop on causal inference and natural language processing accepted to be colocated with EMNLP 2021!

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Working Papers

• • On the Persuasive Power of Reputation in Deliberation Online
  • Emaad Manzoor, George Chen, Dokyun Lee, Michael D. Smith
  • Major revision (first round) at Management Science
  • Resources: Website, Preprint, Discussion slides by Laura K. Nelson
  • Impact: Best paper (e-business cluster) finalist at INFORMS 2019
  • Funding: CMU GuSH Grant / CMU GSA-Provost Grant
  • Talks (2020-2021): AAAI Workshop on AI For Behavior Change (AI4BC) 2021 / Stanford Computational Sociology / MIT IC2S2 / SCECR / Marketing Science Conference / CIST
• • Interpretable Deep Learning for Text Exploration
  • Dokyun Lee, Emaad Manzoor, Zhaoqi Cheng (firstname α-β)
  • Major revision (first round) at Information Systems Research
  • Resources: Website, Preprint
• • Linguistic Determinants of Persuasive Message Elaboration
  • Emaad Manzoor, Dokyun Lee, George H. Chen, Alan L. Montgomery
  • Work in progress
  • Talks (2019): Marketing Science Conference / CIST / INFORMS Workshop on Data Science

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Publications

• • Uncovering Latent Biases in Text
  • Emaad Manzoor, Nihar B. Shah
  • AAAI Conference on Artificial Intelligence (AAAI), 2021
  • Resources: Website, Preprint, Code & Data
  • Talks (2020): INFORMS Workshop on Data Science
• • Detecting Attackable Sentences in Arguments
  • Yohan Jo, Seojin Bang, Emaad Manzoor, Eduard Hovy, Chris Reed
  • Empirical Methods in Natural Language Processing (EMNLP), 2020
  • Resources: Paper, Code & Data
• • Expanding Taxonomies with Implicit Edge Semantics
  • Emaad Manzoor, Dhananjay Shrouty, Rui Li, Jure Leskovec
  • The Web Conference (WWW), 2020
  • Resources: Website, Paper, Code & Data, Slides, Video
  • Impact: External press, Production launch, Patent filed in Oct. ‘19
  • Funding: CMU GSA-Provost Grant
• • xStream: Outlier Detection in Feature-Evolving Data Streams
  • Emaad Manzoor, Hemank Lamba, Leman Akoglu
  • Knowledge Discovery and Data Mining (KDD), 2018
  • Resources: Website, Paper, Code, Data, Slides, Video, Poster
  • Impact: Assigned reading in York University’s Data Mining
  • Funding: CMU GSA-Provost Grant
• • RUSH! Targeted Time-limited Coupons via Purchase Forecasts
  • Emaad Manzoor, Leman Akoglu
  • Knowledge Discovery and Data Mining (KDD), 2017
  • Resources: Paper, Code, Poster
  • Funding: PNC Center for Financial Services Innovation
• • Fast Memory-Efficient Anomaly Detection in Streaming Heterogeneous Graphs
  • Emaad Manzoor, Sadegh M. Milajerdi, Leman Akoglu
  • Knowledge Discovery and Data Mining (KDD), 2016
  • Resources: Website, Paper, Code, Data, Slides, Video, Poster
  • Impact: Assigned reading in the Advanced Computer Security (UIUC, Spring ‘20) and Advanced Data Mining (University of Michigan, Winter ‘19) graduate courses
  • Funding: DARPA Transparent Computing

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Manuscripts

• • Scheduling Broadcasts in a Network of Timelines
  • Emaad Manzoor, Haewoon Kwak, Panos Kalnis
  • Master’s Thesis (KAUST), 2015
  • Resources: Website, Paper, Slides, Video

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Note on Publication Venues

Computer science research is disseminated primarily via conference proceedings. WWW and KDD are flagship conferences of the data mining subdomain (both ranked A* by CORE). EMNLP is one of the top conferences in the natural language processing and computational linguistics subdomain (ranked A* by CORE and based on the Google Scholar h5-index for natural language processing venues). AAAI is one of the top conferences in the artificial intelligence subdomain (ranked A* by CORE and based on the Google Scholar h5-index for artificial intelligence venues).

Academic business research is disseminated primarily via journal publications. Management Science, Marketing Science, Information Systems Research and Management Information Systems Quarterly comprise the highest tier of journals in the information systems and quantitative marketing subdomain (ranked by the Financial Times).