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UBERT: A Novel Language Model for Synonymy Prediction at Scale in the UMLS Metathesaurus ...
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"Is depression related to cannabis?": A Knowledge-infused Model for Entity and Relation Extraction with Limited Supervision
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In: Publications (2021)
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Analyzing and Learning the Language for Different Types of Harassment
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In: Publications (2020)
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ALONE: A Dataset for Toxic Behavior among Adolescents on Twitter
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In: Publications (2020)
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Analyzing and Learning the Language for Different Types of Harassment
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In: Amit P. Sheth (2020)
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ALONE: A Dataset for Toxic Behavior among Adolescents on Twitter
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In: Amit P. Sheth (2020)
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Personalized Prediction of Suicide Risk for Web-based Intervention
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In: Krishnaprasad Thirunarayan (2019)
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Personalized Prediction of Suicide Risk for Web-based Intervention
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In: Amit P. Sheth (2019)
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Personalized Prediction of Suicide Risk for Web-based Intervention
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In: Kno.e.sis Publications (2018)
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Abstract:
Across the United States, suicide is the second leading cause of death for people aged between 15 and 34, and younger people are more prone to mental health problems, suicidal thoughts, and behaviors. For instance, 80% of patients with Borderline Personality Disorder have suicide-related behaviors, and between 4-9% of them commit suicide. Moreover, the social stigma associated with mental health issues and suicide deter patients from sharing their experiences directly with others. In such a situation, social media that provides a free and open forum for voluntary expression can provide insights into suicide ideation and self-destructive behavior. Reddit is a widely used and highly relevant social-media platform where users subscribe to specific subreddits and share their experiences. The users on the respective subreddits often make use of metaphoric suicidal language with related intentions, while interacting with other like-minded users sharing similar experiences. The Columbia-Suicide Severity Rating Scale (C-SSRS) has been employed by clinicians to measure the level of suicidal risk but has not been adequately personalized for improved prevention and resiliency. In this study, we develop a framework for the prediction of suicidal risk by conducting a user-level analysis supervised by C-SSRS and using medical knowledge bases. This will eventually facilitate a clinician to perform a personalized web-based intervention. Our two-fold approach creates a user-level decision-making mechanism that factors in the linguistic, temporal, homophily-based, metaphorical, and intent-based information from the dialogues of 93K users interacting on r/SuicideWatch and other related subreddits that aid in the characterization of users’ suicidal vulnerability.
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Keyword:
Bioinformatics; Communication; Communication Technology and New Media; Computer Sciences; Databases and Information Systems; Life Sciences; OS and Networks; Physical Sciences and Mathematics; Science and Technology Studies; Social and Behavioral Sciences
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URL: https://corescholar.libraries.wright.edu/knoesis/1156 https://corescholar.libraries.wright.edu/cgi/viewcontent.cgi?article=2538&context=knoesis
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Database and Expert Systems Applications - 28th International Conference, DEXA 2017, Lyon, France, Proceedings part II
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In: ISSN: 0302-9743 ; Lecture Notes in Computer Science ; 28th International Conference on Database and Expert Systems Applications and Workshops (DEXA 2017) ; https://hal.archives-ouvertes.fr/hal-03120290 ; Benslimane, Djamal; Damiani, Ernesto; Grosky, William I.; Hameurlain, Abdelkader; Sheth, Amit P.; Wagner, Roland R. 28th International Conference on Database and Expert Systems Applications and Workshops (DEXA 2017), Aug 2017, Lyon, France. Lecture Notes in Computer Science, 10439 (Part II), Springer, 2017, Database and Expert Systems Applications 28th International Conference, DEXA 2017, Lyon, France, 978-3-319-64470-7. ⟨10.1007/978-3-319-64471-4⟩ ; https://link.springer.com/book/10.1007%2F978-3-319-64471-4 (2017)
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RQUERY: Rewriting Natural Language Queries on Knowledge Graphs to Alleviate the Vocabulary Mismatch Problem
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In: Publications (2017)
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RQUERY: Rewriting Natural Language Queries on Knowledge Graphs to Alleviate the Vocabulary Mismatch Problem
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In: Kno.e.sis Publications (2017)
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What Kind of #Communication is Twitter? A Psycholinguistic Perspective on Communication in Twitter for the Purpose of Emergency Coordination
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In: Valerie Shalin (2017)
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What Kind of #Conversation is Twitter? Mining #Psycholinguistic Cues for Emergency Coordination
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In: Valerie Shalin (2017)
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RQUERY: Rewriting Natural Language Queries on Knowledge Graphs to Alleviate the Vocabulary Mismatch Problem
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In: Amit P. Sheth (2017)
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Intent Classification of Short-Text on Social Media
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In: Valerie Shalin (2017)
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Context-Aware Semantic Association Ranking
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In: Amit P. Sheth (2016)
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ezDI's Semantics-Enhanced Linguistic, NLP, and ML Approach for Health Informatics
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In: Amit P. Sheth (2016)
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Intent Classification of Short-Text on Social Media
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In: Amit P. Sheth (2016)
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Intent Classification of Short-Text on Social Media
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In: Krishnaprasad Thirunarayan (2016)
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