Roja Bandari

ORCID: 0000-0002-8522-0904
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About
Contact & Profiles
Research Areas
  • Complex Network Analysis Techniques
  • Opinion Dynamics and Social Influence
  • Spam and Phishing Detection
  • Advanced Text Analysis Techniques
  • Misinformation and Its Impacts
  • Video Analysis and Summarization
  • Energy Efficient Wireless Sensor Networks
  • Digital Humanities and Scholarship
  • Data Visualization and Analytics
  • Vaccine Coverage and Hesitancy
  • Social Media and Politics
  • Media Studies and Communication
  • Influenza Virus Research Studies
  • Healthcare professionals’ stress and burnout
  • Speech and Audio Processing
  • Environmental Monitoring and Data Management
  • Web Data Mining and Analysis
  • Resilience and Mental Health
  • Indoor and Outdoor Localization Technologies
  • Wireless Sensor Networks for Data Analysis
  • Workplace Health and Well-being
  • Modular Robots and Swarm Intelligence
  • Target Tracking and Data Fusion in Sensor Networks
  • Sensor Technology and Measurement Systems

University of California, Los Angeles
2012-2021

UCLA Health
2010

News articles are extremely time sensitive by nature. There is also intense competition among news items to propagate as widely possible. Hence, the task of predicting popularity on social web both interesting and challenging. Prior research has dealt with eventual online based early popularity. It most desirable, however, predict prior their release, fostering possibility appropriate decision making modify an article manner its publication. In this paper, we construct a multi-dimensional...

10.1609/icwsm.v6i1.14261 article EN Proceedings of the International AAAI Conference on Web and Social Media 2021-08-03

News articles are extremely time sensitive by nature. There is also intense competition among news items to propagate as widely possible. Hence, the task of predicting popularity on social web both interesting and challenging. Prior research has dealt with eventual online based early popularity. It most desirable, however, predict prior their release, fostering possibility appropriate decision making modify an article manner its publication. In this paper, we construct a multi-dimensional...

10.48550/arxiv.1202.0332 preprint EN other-oa arXiv (Cornell University) 2012-01-01

Social media offer an unprecedented opportunity to explore how people talk about health care at a very large scale. Numerous studies have shown the importance of websites with user forums for seeking information related health. Parents turn some these sites, colloquially referred as "mommy blogs," share concerns children's care, including vaccination. Although substantial work has considered role social media, particularly Twitter, in discussions vaccination and other care-related issues,...

10.2196/publichealth.6586 article EN cc-by JMIR Public Health and Surveillance 2016-11-22

Twitter has undoubtedly caught the attention of both general public, and academia as a microblogging service worthy study attention. several features that sets it apart from other social media/networking sites, including its 140 character limit on each user's message (tweet), unique combination avenues via which information is shared: directed network friends followers, where messages posted by user broadcast to all public timeline, provides real time access posts or tweets specific topics...

10.1145/1964858.1964875 article EN 2010-07-25

An analysis of more than eight years data from vaccination forums on mothering.com shows that the antivaccination movement is well-organized and widely dispersed, it emerged long before concerns about immunity were expressed. The findings are evidence a formidable challenge to social norms surrounding vaccination.

10.1109/mc.2017.4041354 article EN Computer 2017-11-01

Reader reviews of literary fiction on social media, especially those in persistent, dedicated forums, create and are turn driven by underlying narrative frameworks. In their comments about a novel, readers generally include only subset characters relationships, thus offering limited perspective that work. Yet aggregate, these capture an framework comprised different actants (people, places, things), roles, interactions we label the "consensus framework". We represent this form...

10.1145/3394231.3397918 article EN 2020-06-23

Objective: To examine the relationship between mental health treatment and employee retention. Study Design: Retrospective Cohort Methods: 14 companies (184,715 employees) were studied evaluating retention among individuals who used an evidence-based benefit. Among three provided plan claims (n=24,947), we compared 1,966 employees benefit 1,063 had usual care. Survival analysis was to compare probability of staying at company for two cohorts. Cox Proportional Hazards Models evaluate hazard...

10.18103/mra.v9i11.2574 article EN Medical Research Archives 2021-01-01

We propose an automated and unsupervised methodology for a novel summarization of group behavior based on content preference. show that graph theoretical community evolution (based similarity user preference content) is effective in indexing these dynamics. Combined with text analysis targets automatically-identified representative each community, our method produces multi-layered representation evolving behavior. demonstrate this the context political discourse social news site data spans...

10.48550/arxiv.1304.1567 preprint EN other-oa arXiv (Cornell University) 2013-01-01

Reader reviews of literary fiction on social media, especially those in persistent, dedicated forums, create and are turn driven by underlying narrative frameworks. In their comments about a novel, readers generally include only subset characters relationships, thus offering limited perspective that work. Yet aggregate, these capture an framework comprised different actants (people, places, things), roles, interactions we label the "consensus framework". We represent this form...

10.48550/arxiv.2004.09601 preprint EN other-oa arXiv (Cornell University) 2020-01-01

We propose an automated and unsupervised methodology for a novel summarization of group behavior based on content preference. show that graph theoretical community evolution (based similarity user preference content) is effective in indexing these dynamics. Combined with text analysis targets automatically-identified representative each community, our method produces multi-layered representation evolving behavior. demonstrate this the context political discourse social news site data spans...

10.1609/icwsm.v7i1.14433 article EN Proceedings of the International AAAI Conference on Web and Social Media 2021-08-03
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