Dear All,
We are the guest editors of the special issue “Mathematical and Computational Modeling of Language and Social Behaviors” in Mathematics<https://www.mdpi.com/journal/mathematics> (IF=2.592, Q1). We would like to call for papers to the above special issue from people whose research interest include computational linguistics and the related areas. Deadline for manuscript submissions: 30 June 2023. The aim of the special issue is to highlight the contributions of quantitative modeling and NLP technology to understanding collective human behaviors and to help resolve some of the greatest challenges of our time. We welcome new or improved methods to model linked data from heterogeneous sources and their computational application to solve some real-world problems relating to languages and social behaviors. Topics of interest include such as Sentiment and/or Emotion Analysis, fake news detection, FinNLP and Medical Informatics. Check the details about the special issue through the link: https://www.mdpi.com/si/mathematics/Mathe_Compu_NLP We look forward to your submissions and contribution to this special issue. Thank you very much! Best, Clara (on behalf of the Guest Editors) [https://www.polyu.edu.hk/emaildisclaimer/85A-PolyU_Email_Signature.jpg] Disclaimer: This message (including any attachments) contains confidential information intended for a specific individual and purpose. If you are not the intended recipient, you should delete this message and notify the sender and The Hong Kong Polytechnic University (the University) immediately. Any disclosure, copying, or distribution of this message, or the taking of any action based on it, is strictly prohibited and may be unlawful. The University specifically denies any responsibility for the accuracy or quality of information obtained through University E-mail Facilities. Any views and opinions expressed are only those of the author(s) and do not necessarily represent those of the University and the University accepts no liability whatsoever for any losses or damages incurred or caused to any party as a result of the use of such information.
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