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20122020
most citedComparing Suicide Risk Insights derived from Clinical and Social Media data

1 citations · 1 across the 3 of their papers we have counts for

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cs.SI2020★ 1 cited

Comparing Suicide Risk Insights derived from Clinical and Social Media data

Rohith K. Thiruvalluru, Manas Gaur, Krishnaprasad Thirunarayan +2

Suicide is the 10th leading cause of death in the US and the 2nd leading cause of death among teenagers. Clinical and psychosocial factors contribute to suicide risk (SRFs), althou…

cs.SI2020

Exo-SIR: An Epidemiological Model to Analyze the Impact of Exogenous Infection of COVID-19 in India

Nirmal Kumar Sivaraman, Manas Gaur, Shivansh Baijal +3

Epidemiological models are the mathematical models that capture the dynamics of epidemics. The spread of the virus has two routes - exogenous and endogenous. The exogenous spread i…

cs.SI2020

Depressive, Drug Abusive, or Informative: Knowledge-aware Study of News Exposure during COVID-19 Outbreak

Amanuel Alambo, Manas Gaur, Krishnaprasad Thirunarayan

The COVID-19 pandemic is having a serious adverse impact on the lives of people across the world. COVID-19 has exacerbated community-wide depression, and has led to increased drug…

cs.SI2019

Unsupervised Detection of Sub-events in Large Scale Disasters

Chidubem Arachie, Manas Gaur, Sam Anzaroot +3

Social media plays a major role during and after major natural disasters (e.g., hurricanes, large-scale fires, etc.), as people ``on the ground'' post useful information on what is…

cs.SI2018

empathi: An ontology for Emergency Managing and Planning about Hazard Crisis

Manas Gaur, Saeedeh Shekarpour, Amelie Gyrard +1

In the domain of emergency management during hazard crises, having sufficient situational awareness information is critical. It requires capturing and integrating information from…

cs.SI2018

What's my age?: Predicting Twitter User's Age using Influential Friend Network and DBpedia

Alan Smith, Manas Gaur

Social media is a rich source of user behavior and opinions. Twitter senses nearly 500 million tweets per day from 328 million users.An appropriate machine learning pipeline over t…