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Laboratory for Computational Social Systems (LCS2) is a research group led by Dr. Tanmoy Chakraborty and Dr. Md. Shad Akhtar at Indraprastha Institute of Information Technology, Delhi (IIIT-Delhi). Broad research interests of this group include Data Mining, Complex Networks, Social Computing, Natural Language Processing and Data-driven Cybersecurity.

Data Science for Fake News

News

  • May 11, 2021
    Dr. Tanmoy Chakraborty has received a faculty research grant from LinkedIn to work on issues related to misinformation.
  • May 06, 2021
    Paper accepted in ACL Findings, 2021 Shraman Pramanick, Dimitar Dimitrov, Rituparna Mukherjee, Shivam Sharma, Md. Shad Akhtar, Preslav Nakov, Tanmoy Chakraborty. Detecting Harmful Memes and Their Targets .
  • May 06, 2021
    Paper accepted in ACL Findings, 2021 Nirav Diwan, Tanmoy Chakraborty, Zubair Shafiq. Fingerprinting Fine-tuned Language Models in the Wild .
  • May 06, 2021
    Paper accepted in ACL Findings, 2021 Ayan Sengupta, Sourabh Kumar Bhattacharjee, Tanmoy Chakraborty, Md. Shad Akhtar. HIT - A Hierarchically Fused Deep Attention Network for Robust Code-mixed Language Representation .
  • April 27, 2021
    Paper accepted in IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021 Kaiqiang Yu, Cheng Long, Deepak P, Tanmoy Chakraborty. On Efficient Large Maximal Biplex Discovery .
  • April 16, 2021
    Paper accepted in IEEE Transactions on Computational Social Systems Suraj Pandey, Md Shad Akhtar, Tanmoy Chakraborty. Syntactically Coherent Text Augmentation for Sequence Classification .
  • April 14, 2021
    Tutorial accepted in ECML-PKDD 2021: Sarah Masud, Pinkesh Badjatiya, Amitava Das, Manish Gupta, Vasudeva Varma, Tanmoy Chakraborty. Combating Online Hate Speech: Roles of Content, Networks, Psychology, User Behavior and Others .
  • April 09, 2021
    Paper accepted in Applied Soft Computing: William Scott Paka, Rachit Bansal, Abhay Kaushik, Shubhashis Sengupta, Tanmoy Chakraborty. Cross-SEAN: A Cross-Stitch Semi-Supervised Neural Attention Model for COVID-19 Fake News Detection .

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