Julina Maharjan

Julina Maharjan

(She/Her)

PhD Candidate in Computer Science

Posts by Collection

portfolio

publications

Large-Scale Deep Learning–Enabled Infodemiological Analysis of Substance Use Patterns on Social Media: Insights From the COVID-19 Pandemic

Published in J Med Internet Res 2024, 2024

The COVID-19 pandemic intensified the challenges associated with mental health and substance use (SU), with societal and economic upheavals leading to heightened stress and increased reliance on drugs as a coping mechanism. Centers for Disease Control and Prevention data from June 2020 showed that 13% of Americans used substances more frequently due to pandemic-related stress, accompanied by an 18% rise in drug overdoses early in the year. Simultaneously, a significant increase in social media engagement provided unique insights into these trends. Our study analyzed social media data from January 2019 to December 2021 to identify changes in SU patterns across the pandemic timeline, aiming to inform effective public health interventions.

Recommended citation: Maharjan J, Zhu J, King J, Phan N, Kenne D, Jin R Large-Scale Deep Learning–Enabled Infodemiological Analysis of Substance Use Patterns on Social Media: Insights From the COVID-19 Pandemic JMIR Infodemiology 2025;5:e59076
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Differential Analysis of Age, Gender, Race, Sentiment, and Emotion in Substance Use Discourse on Twitter during the COVID-19 Pandemic: An NLP Approach

Published in JMIR (Journal of Medical Internet Research) 2024, 2024

User Demographics are often hidden in social media data due to privacy concerns. However, demographic information on Substance Use can provide valuable insights, allowing Public Health policymakers to focus on specific cohorts and develop efficient prevention strategies, especially during global crises like COVID-19.

Recommended citation: Maharjan J, Jin R, King J, Zhu J, Kenne D Differential Analysis of Age, Gender, Race, Sentiment, and Emotion in Substance Use Discourse on Twitter during the COVID-19 Pandemic: An NLP Approach JMIR Preprints. 08/10/2024:67333
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talks

Big Data and Hadoop Training

Published:

Conducted a workshop for 3rd-year Computer Science students at Deerwalk Institute of Technology, Kathmandu, Nepal. Trained students on Hadoop architecture, data processing, and distributed computing techniques.

teaching

Teaching Assistant for Computer Programming (C++)

Undergraduate course, Kent State University, Computer Department, 2019

  • Assisted in teaching C++ programming to undergraduate students.
  • Conducted lab sessions, guided students in debugging and optimizing code, and explained core data structures and algorithms.
  • Provided one-on-one tutoring and graded programming assignments, ensuring students understood best coding practices.

Teaching Assistant – Data Structures

Workshop, Kent State University, Computer Department, 2020

  • Assisted in teaching fundamental and advanced data structures to undergraduate students.
  • Conducted lab sessions, helping students implement linked lists, trees, graphs, hash tables, and sorting algorithms.
  • Provided one-on-one tutoring and graded assignments, ensuring students understood algorithm efficiency (Big O notation) and best coding practices.
  • Guided students in debugging and optimizing C++/Java code, preparing them for real-world software engineering challenges.