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X-WR-CALDESC:Events for USC Big Data Health Science Center
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DTSTART;VALUE=DATE:20211101
DTEND;VALUE=DATE:20211102
DTSTAMP:20260611T112502
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SUMMARY:BDHS Conference: Abstract Submission Deadline
DESCRIPTION:The Big Data Health Science Center is seeking abstract submissions for its 3rd annual National Big Data Health Science Conference. The theme of the conference is “Unlocking the Power of Big Data in Health: Developing an Interdisciplinary Response for Health Equity“. The conference will be held in Columbia\, SC (virtual option available) on February 11-12\, 2022.  \nResearch and program-based abstracts in the areas of AI\, COVID-19\, EHR\, social media data\, genomics data\, geospatial data\, infrastructural and capacity development\, professional development\, community/industry engagement\, academic training\, and methodological advances are desired. Students are encouraged to submit abstracts for poster presentations. \nThe deadline for submissions is November 1\, 2021. For more information or to submit your abstract\, visit https://www.sc-bdhs-conference.org/abstract-2022/ \n 
URL:https://bigdata.sc.edu/event/bdhs-conference-abstract-submission-deadline/
CATEGORIES:Conference
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UID:4174-1637146800-1637150400@bigdata.sc.edu
SUMMARY:Employing Social Media to Improve Mental Health: Pitfalls\, Lessons Learned\, and the Next Frontier
DESCRIPTION:The BDHSC Social Media Core is hosting Dr. Munmun De Choudhurry for a virtual seminar titled “Employing Social Media to Improve Mental Health: Pitfalls\, Lessons Learned\, and the Next Frontier”. \nThe seminar will be held virtually via Zoom on November 17\, 2021 from 11:00am-12:00pm.  \nRegister at https://bit.ly/3bucMln \nAbout the Seminar: Social media data is being increasingly used to computationally learn about and infer the mental health states of individuals and populations. Despite being touted as a powerful means to shape interventions and impact mental health recovery\, we understand little about the theoretical\, domain\, and psychometric validity of this novel information source\, or its underlying biases\, when appropriated to augment conventionally gathered data\, such as surveys and verbal self-reports. \nThis talk presents a critical analytic perspective on the pitfalls of social media signals of mental health\, especially when they are derived from “proxy” diagnostic indicators\, often removed from the real-world context in which they are likely to be used. To overcome these pitfalls\, this talk presents results from two case studies (forecasting schizophrenia relapse and populational-level rates of suicide fatalities)\, where machine learning algorithms to glean mental health insights from social media were developed in a context-sensitive and human-centered way\, in collaboration with domain experts and stakeholders. \nThe talk concludes with discussions of the path forward\, emphasizing the need for a collaborative\, multi-disciplinary research agenda while realizing the potential of social media data and machine learning in mental health — one that incorporates methodological rigor\, ethics\, and accountability\, all at once. \nAbout the Speaker: Munmun De Choudhury is an Associate Professor of Interactive Computing at Georgia Tech. Dr. De Choudhury is best known for laying the foundation of a line of research that develops computational techniques to responsibly and ethically employ social media in understanding and improving our mental health. To do this work\, she adopts a highly interdisciplinary approach\, combining social computing\, machine learning\, and natural language analysis with insights and theories from the social\, behavioral\, and health sciences. Dr. De Choudhury has been recognized with the 2021 ACM-W Rising Star Award\, 2019 Complex Systems Society – Junior Scientific Award\, numerous best paper and honorable mention awards from the ACM and AAAI\, and features and coverage in popular press like the New York Times\, the NPR\, and the BBC. Earlier\, Dr. De Choudhury was a faculty associate with the Berkman Klein Center for Internet and Society at Harvard\, a postdoc at Microsoft Research\, and obtained her PhD in Computer Science from Arizona State University.
URL:https://bigdata.sc.edu/event/employing-social-media-to-improve-mental-health-pitfalls-lessons-learned-and-the-next-frontier/
CATEGORIES:Seminar
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