Zobrazeno 1 - 10
of 87
pro vyhledávání: '"Md. Shad Akhtar"'
Publikováno v:
Humanities & Social Sciences Communications, Vol 11, Iss 1, Pp 1-12 (2024)
Abstract The advent of globalization and adaptation to multiple cultures has emanated a fusion of Hindi and English, casually known as Hinglish. The phenomenon of mixing multiple languages (such as Hindi and English) within a single utterance is ofte
Externí odkaz:
https://doaj.org/article/dd04d2643250465bb49e5749ec007773
Publikováno v:
IEEE Transactions on Computational Social Systems. :1-11
Publikováno v:
Proceedings of the ACM Web Conference 2023.
Virtual Mental Health Assistants (VMHAs) have become a prevalent method for receiving mental health counseling in the digital healthcare space. An assistive counseling conversation commences with natural open-ended topics to familiarize the client wi
Publikováno v:
Computational Linguistics and Intelligent Text Processing ISBN: 9783031243394
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::152f9305fd0d5d0245570fc103e52483
https://doi.org/10.1007/978-3-031-24340-0_18
https://doi.org/10.1007/978-3-031-24340-0_18
Publikováno v:
IEEE Transactions on Computational Social Systems. 8:1323-1332
In this article, we address the problem of data scarcity for the sequence classification tasks. We propose AugmentGAN, a simple-yet-effective generative adversarial network-based text augmentation model, which ensures syntactic coherency in the newly
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Autor:
Usha Lokala, Aseem Srivastava, Triyasha Ghosh Dastidar, Tanmoy Chakraborty, Md Shad Akhtar, Maryam Panahiazar, Amit Sheth
Analyzing gender is critical to study mental health (MH) support in CVD (cardiovascular disease). The existing studies on using social media for extracting MH symptoms consider symptom detection and tend to ignore user context, disease, or gender. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::420d6ee8096ba91c02d5b8b3dbf7bb54
http://arxiv.org/abs/2203.11856
http://arxiv.org/abs/2203.11856
Autor:
Shivam Sharma, Firoj Alam, Md. Shad Akhtar, Dimitar Dimitrov, Giovanni Da San Martino, Hamed Firooz, Alon Halevy, Fabrizio Silvestri, Preslav Nakov, Tanmoy Chakraborty
Publikováno v:
Scopus-Elsevier
The automatic identification of harmful content online is of major concern for social media platforms, policymakers, and society. Researchers have studied textual, visual, and audio content, but typically in isolation. Yet, harmful content often comb
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::87b6c7d603573bf51b52a5fa24513760
https://hdl.handle.net/11577/3481486
https://hdl.handle.net/11577/3481486
Curbing online hate speech has become the need of the hour; however, a blanket ban on such activities is infeasible for several geopolitical and cultural reasons. To reduce the severity of the problem, in this paper, we introduce a novel task, hate s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7af8a11fb46879be6c840f8e2da8068c
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031116438
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e21e8ccd09f73f95a0ff22bc1db75d4
https://doi.org/10.1007/978-3-031-11644-5_39
https://doi.org/10.1007/978-3-031-11644-5_39