< Ghazaleh Beigi

I'm a fifth year Ph.D. Candidate at Data Mining and Machine Learning Lab, Arizona State University under supervision of Professor Huan Liu. My research is focused on leveraging machine learning/data mining techniques for discovering, understanding and modeling implicit signals in online users behavior.

In Summer 2019, I interned at Google as a Software Engineer in the Core Computing Analytics team at Google Cloud (Sunnyvale, CA).

Before joining ASU as a Ph.D. student in Fall 2014, I earned my Bachelor's and Master's degrees from Sharif University of Technology in Summer 2013 and Summer 2014, respectively.

My research interests include:

  • User privacy protection
  • Signed network analysis
  • Trust and distrust prediction
  • Recommendation Systems
  • Sentiment analysis
  • User behavior modeling
  • Machine learning and data mining

My research (WSDM 2019) is featured in The Morning Paper blog.

A blog about my research, "A Non-Compromising Approach to Privacy-Preserving Personalized Services", is now posted on KDNuggets.

My recent research on web browsing history anonymization which is accepted in the WSDM 2019, was featured in the news: The data defenders.

We also prepared a comprehensive survey on privacy in social media. It could be found here.

This is also my CV .
Email: gbeigi at asu dot edu

Publication

Conference Papers:

  • Beigi, G., Mosallanezhad, A., Guo, R., Alvari, H., Nou, A., Liu, H.: ’Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning’. [PDF]
    In the 13th ACM International Conference on Web Search and Data Mining (WSDM-2020)
  • Mosallanezhad, A., Beigi, G., Liu, H.: ’Deep Reinforcement Learning-based Text Anonymization Against Private-Attribute Inference’.[PDF]
    In the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP'19).
  • Beigi, G., Shu, K., Guo, R., Wang, S., Liu, H.: ’Privacy Preserving Text Representation Learning’.
    [PDF] [Long Version]
    In the 30th ACM Conference on HyperText and Social Media (HT'19).
  • Beigi, G., Ranganath, S., Liu, H.: ’Signed Link Prediction with Sparse Data: The Role of Personality Information’.[PDF]
    In Companion of the Proceedings of The Web Conference (WWW'19).
  • Alvari, H., Shaabani, E., Sarkar, S., Beigi, G., Shakarian, P.: ’Less is More: Semi-Supervised Causal Inference for Detecting Pathogenic Users in Social Media’.[PDF]
    In Companion of the Proceedings of The Web Conference (WWW'19).
  • Beigi, G., Liu, H.: ’Identifying novel privacy issues of online users on social media platforms’. [PDF]
    In the ACM SIGWEB Newsletter, Winter, 2019
  • Beigi, G., Guo, R., Nou, A., Zhang, Y., Liu, H.: ’Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles’. [PDF]
    In the 12th ACM International Conference on Web Search and Data Mining (WSDM-2019)
  • Kamarudin, N., Rakesh, V., Beigi, G., Manikonda, L., Liu, H.: ’A Study of Reddit-User's Response to Rape’. [PDF]
    In the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM - 2018)
  • Beigi, G., Shu, K., Liu, H.: ’Securing Social Media User Data - An Adversarial Approach’. [PDF]
    In the 29th ACM Conference on HyperText and Social Media (HT-2018)
  • Beigi, G., Liu, H.: ’Similar But Different: Exploiting Users Congruity for Recommendation Systems’. [PDF]
    In the 2018 International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-18).
  • Manikonda, L., Beigi, G., Liu, H.: ’Twitter for Sparking a Movement, Reddit for Sharing the Moment: #metoo through the Lens of Social Media’.
    In the 2018 International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-18).
  • Ranganath, S., Beigi, G., Liu, H.: ’Leveraging Implicit Contribution Amounts to Facilitate Microfinancing Requests’.[PDF]
    In the 11th ACM International Conference on Web Search and Data Mining (WSDM-18).
  • Beigi, G., Tang, J., Liu, H.: ’Signed Link Analysis in Social Media Networks’.[PDF]
    In the 10th International AAAI Conference on Web and Social Media (ICWSM-16).
  • Beigi, G., Tang, J.,Wang, S., Liu, H.: ’Exploiting Emotional Information for Trust/Distrust Prediction’.[PDF]
    In SIAM International Conference on Data Mining (SDM-2016).
  • Beigi, G., Jalili, M., Alvari, H., Sukthankar, G.: ’Leveraging Community Detection for Accurate Trust Prediction’. [PDF]
    In the Sixth ASE International Conference on Social Computing (ICSC-2014).

Survey Papers:

  • Beigi, G., Liu, H.: ’A Survey on Privacy in Social Media: Identification, Mitigation and Applications’. [PDF]
    To be published in the ACM Transaction on Data Science (TDS-2019)

Journal Papers:

  • Beigi, G., Tang, J., Liu, H.: ’Social Science Guided Feature Engineering: A Novel Approach to Signed Link Analysis’.[PDF]
    In the Journal of ACM Transactions on Intelligent Systems and Technology (ACM TIST- 2019).
  • Kamarudin, N., Beigi, G., Rakesh, V., Manikonda, L., Liu, H.: ’Treasure Trove of Online Forum: Nuggets Discovered from User Response to Rape Discussions through Reddit’.
    To be submitted

Book Chapters:

  • Kamarudin, N., Beigi, G., Manikonda, L., Liu, H.: ’Social Media- A New and Effective Platform for Raising Awareness of Mental Health Issues’.
    Accepted for inclusion in the edited volume entitled as Open Source Intelligence and Security Informatics. Published by Springer (2019).
  • Beigi, G., Hu, X., Maciejewski, R., Liu, H.: ’An Overview of Sentiment Analysis in Social Media and its Applications in Disaster Relief’.[PDF]
    In edited volume entitled as Sentiment Analysis and Ontology Engineering: An Environment of Computational Intelligence. Published by Springer. Editors: Shyi-Ming Chen and Witold Pedrycz (2016)

Theses:

  • Beigi, G.: ’Leveraging User-Item Interactions for Trust Prediction’. M.Sc. Thesis (in Persian),
    Computer Engineering Department, Sharif University of Technology, July 2014.
  • Beigi, G.: ’Community Detection in Social Networks’. B.Sc. Thesis (in Persian),
    Computer Engineering Department, Sharif University of Technology, June 2013.

Services

Programm Committee

  • Conferences: SBP

Conference/Journal Reviews

  • Conferences: KDD, AAAI, IJCAI, WWW, WSDM, SDM, ICDM, SIGIR, RecSys, ICWSM, ASONAM.
  • Journal and book chapter: ACM Transactions on Data Science, IEEE Intelligent Systems, IEEE Transactions on Big Data, Social Network Analysis and Mining Journal (SNAM), Sentiment Analysis and Ontology Engineering: An Environment of Computational Intelligence

Contact

Ghazaleh Beigi

Data Mining and Machine Learning Lab
699 S Mill Ave
Room 561
Tempe AZ-85281

Email: gbeigi at asu dot edu