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Evolution and differentiation of the cybersecurity communities in three social question and answer sites: A mixed-methods analysis.
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In: PloS one, vol 16, iss 12 (2021)
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Piloting an integrated SARS-CoV-2 testing and data system for outbreak containment among college students: A prospective cohort study.
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In: PloS one, vol 16, iss 1 (2021)
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Piloting an integrated SARS-CoV-2 testing and data system for outbreak containment among college students: A prospective cohort study.
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In: PloS one, vol 16, iss 1 (2021)
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Effect of voicing and articulation manner on aerosol particle emission during human speech.
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In: PloS one, vol 15, iss 1 (2020)
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A human-machine partnered approach for identifying social media signals of elevated traumatic grief in Chicago gang territories.
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In: PloS one, vol 15, iss 7 (2020)
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Abstract:
There is a critical need to improve trauma-informed services in structurally marginalized communities impacted by violence and its associated traumatic grief. For community residents, particularly gang-associated youth, repeated exposure to traumatic grief causes serious adverse effects that may include negative health outcomes, delinquency, and future violent offenses. The recent proliferation of digital social media platforms, such as Twitter, provide a novel and largely underutilized resource for responding to these issues, particularly among these difficult-to-reach communities. In this paper, we explore the potential for using a human-machine partnered approach, wherein qualitative fieldwork and domain expertise is combined with a computational linguistic analysis of Twitter content among 18 gang territories/neighborhoods on Chicago's South Side. We first employ in-depth interviews and observations to identify common patterns by which residents in gang territories/neighborhoods express traumatic grief on social media. We leverage these qualitative findings, supplemented by domain expertise and computational techniques, to gather both traumatic grief- and gang-related tweets from Twitter. We next utilize supervised machine learning to construct a binary classification algorithm to eliminate irrelevant tweets that may have been gathered by our automated query and extraction techniques. Last, we confirm the validity, or ground truth, of our computational findings by enlisting additional domain expertise and further qualitative analyses of the specific traumatic events discussed in our sample of Twitter content. Using this approach, we find that social media provides useful signals for identifying moments of increased collective traumatic grief among residents in gang territories/neighborhoods. This is the first study to leverage Twitter to systematically ground the collective online articulations of traumatic grief in traumatic offline events occurring in violence-impacted communities. The results of this study will be useful for developing more effective tools-including trauma-informed intervention applications-for community organizations, violence prevention initiatives, and other public health efforts.
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Keyword:
Algorithms; Chicago; General Science & Technology; Grief; Humans; Residence Characteristics; Social Media; Violence
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URL: https://escholarship.org/uc/item/4dc3q8rd
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| 6 |
A human-machine partnered approach for identifying social media signals of elevated traumatic grief in Chicago gang territories.
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In: PloS one, vol 15, iss 7 (2020)
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Three-dimensional vocal fold structural change due to implant insertion in medialization laryngoplasty.
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In: PloS one, vol 15, iss 1 (2020)
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Differential asthma odds following respiratory infection in children from three minority populations.
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In: PloS one, vol 15, iss 5 (2020)
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Differential asthma odds following respiratory infection in children from three minority populations.
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In: PloS one, vol 15, iss 5 (2020)
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| 10 |
Cake or broccoli? Recency biases children's verbal responses.
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In: PloS one, vol 14, iss 6 (2019)
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| 11 |
Status, identity, and language: A study of issue discussions in GitHub.
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In: PloS one, vol 14, iss 6 (2019)
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Mitogenomes illuminate the origin and migration patterns of the indigenous people of the Canary Islands.
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In: PloS one, vol 14, iss 3 (2019)
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Small changes, big gains: A curriculum-wide study of teaching practices and student learning in undergraduate biology.
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In: PloS one, vol 14, iss 8 (2019)
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| 14 |
The Classroom Discourse Observation Protocol (CDOP): A quantitative method for characterizing teacher discourse moves in undergraduate STEM learning environments.
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In: PloS one, vol 14, iss 7 (2019)
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| 15 |
Brain basis of cognitive resilience: Prefrontal cortex predicts better reading comprehension in relation to decoding.
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In: PloS one, vol 13, iss 6 (2018)
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Dynamic integration of conceptual information during learning.
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In: PloS one, vol 13, iss 11 (2018)
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Y chromosomal evidence on the origin of northern Thai people.
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In: PloS one, vol 12, iss 7 (2017)
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Executive function, visual attention and the cocktail party problem in musicians and non-musicians
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| 19 |
High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings.
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In: PloS one, vol 11, iss 3 (2016)
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Survivorship Care Plan Information Needs: Perspectives of Safety-Net Breast Cancer Patients.
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In: PloS one, vol 11, iss 12 (2016)
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