Shailik Sarkar

According to our database, Shailik Sarkar authored at least 10 papers between 2021 and 2023.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2023

More than Just a Diagnosis: A Multi-Task Approach to Analyzing Bipolar Disorder on Reddit via DeMHeM.

Rocco Zhang, Shailik Sarkar, Abdulaziz Alhamadani, Chang-Tien Lu

Proceedings of the IEEE International Conference on Big Data, 2023

Hypergraph Text Classification for Mental Health Misleading Advice.

Lulwah Alkulaib, Abdulaziz Alhamadani, Shailik Sarkar, Chang-Tien Lu

Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2023

From Guest to Family: An Innovative Framework for Enhancing Memorable Experiences in the Hotel Industry.

Abdulaziz Alhamadani, Khadija Althubiti, Shailik Sarkar, Jianfeng He, Lulwah Alkulaib, Srishti Behal, Mahmood Khan, Chang-Tien Lu

Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2023

2022

Explainable Prediction of the Severity of COVID-19 Outbreak for US Counties.

Shailik Sarkar, Abdulaziz Alhamadani, Chang-Tien Lu

Proceedings of the IEEE International Conference on Big Data, 2022

HyperTwitter: A Hypergraph-based Approach to Identify Influential Twitter Users and Tweets.

Lulwah Alkulaib, Abdulaziz Alhamadani, Shailik Sarkar, Chang-Tien Lu

Proceedings of the IEEE International Conference on Big Data, 2022

DOD-Explainer: Explainable Drug Overdose Deaths Predictor from Crime and Socioeconomic Data.

Abdulaziz Alhamadani, Shailik Sarkar, Lulwah Alkulaib, Chang-Tien Lu

Proceedings of the IEEE International Conference on Big Data, 2022

Predicting Depression and Anxiety on Reddit: a Multi-task Learning Approach.

Shailik Sarkar, Abdulaziz Alhamadani, Lulwah Alkulaib, Chang-Tien Lu

Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2022

PRISTINE: Semi-supervised Deep Learning Opioid Crisis Detection on Reddit.

Abdulaziz Alhamadani, Shailik Sarkar, Lulwah Alkulaib, Chang-Tien Lu

Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2022

2021

Forecasting High-risk Areas of COVID-19 Infection Through Socioeconomic and Static Spatial Analysis.

Abdulaziz Alhamadani, Shailik Sarkar, Lei Zhang, Lulwah Alkulaib, Chang-Tien Lu

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information.

Padmaksha Roy, Shailik Sarkar, Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu

Proceedings of the ASONAM '21: International Conference on Advances in Social Networks Analysis and Mining, Virtual Event, The Netherlands, November 8, 2021