no code implementations • 23 Nov 2023 • Sumit Dalal, Deepa Tilwani, Manas Gaur, Sarika Jain, Valerie Shalin, Amit Seth
We develop such a system in the context of MH using clinical practice guidelines (CPG) for diagnosing depression, a mental health disorder of global concern.
no code implementations • 10 May 2020 • Shreyansh Bhatt, Amit Sheth, Valerie Shalin, Jinjin Zhao
Intelligent systems designed using machine learning algorithms require a large number of labeled data.
no code implementations • 18 Aug 2019 • Ugur Kursuncu, Manas Gaur, Carlos Castillo, Amanuel Alambo, K. Thirunarayan, Valerie Shalin, Dilshod Achilov, I. Budak Arpinar, Amit Sheth
Our study makes three contributions to reliable analysis: (i) Development of a computational approach rooted in the contextual dimensions of religion, ideology, and hate that reflects strategies employed by online Islamist extremist groups, (ii) An in-depth analysis of relevant tweet datasets with respect to these dimensions to exclude likely mislabeled users, and (iii) A framework for understanding online radicalization as a process to assist counter-programming.
no code implementations • 26 Feb 2018 • Mohammadreza Rezvan, Saeedeh Shekarpour, Lakshika Balasuriya, Krishnaprasad Thirunarayan, Valerie Shalin, Amit Sheth
In this paper, we publish first, a quality annotated corpus and second, an offensive words lexicon capturing different types type of harassment as (i) sexual harassment, (ii) racial harassment, (iii) appearance-related harassment, (iv) intellectual harassment, and (v) political harassment. We crawled data from Twitter using our offensive lexicon.
1 code implementation • COLING 2018 • Hussein S. Al-Olimat, Krishnaprasad Thirunarayan, Valerie Shalin, Amit Sheth
Extracting location names from informal and unstructured social media data requires the identification of referent boundaries and partitioning compound names.
no code implementations • 19 Jan 2017 • Saeedeh Shekarpour, Faisal Al-Shargi, Valerie Shalin, Krishnaprasad Thirunarayan, Amit P. Sheth
These use-cases demonstrate the benefits of using CEVO for annotation: (i) annotating English verbs from an abstract conceptualization, (ii) playing the role of an upper ontology for organizing ontological properties, and (iii) facilitating the annotation of text relations using any underlying vocabulary.