Say Their Names: Resurgence in the collective attention toward Black victims of fatal police violence following the death of George Floyd

Wu, Haonan; Gallagher, Ryan J.; Alshaabi, Thayer; Adams, Jane Lydia; Minot, Joshua R.; Arnold, Michael Vincent; Welles, Brooke Foucault; Harp, Randall; Dodds, Peter Sheridan; Danforth, Christopher M.

doi:10.48550/arxiv.2106.10281

Cited by 5 publications

(5 citation statements)

References 33 publications

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“…Results demonstrated that English language Hedonometer scores exhibited only trend-level significance, suggesting that proximity (physical, and likely emotional) to the geographical location of the event effects the strength of the association between community-level mood and likelihood of experiencing a panic attack. Acknowledging that individual wellbeing is affected by societal events is consistent with previous literature [16,17][28], and in this particular case of panic attacks, demonstrates that individual physiology is acutely impacted. This association between individual physiology and societal events may be strengthened in individuals who experience regular panic attacks and as anxious individuals may pay more attention to negative occurrences in the news [29][30].…”

Section: Discussionsupporting

confidence: 89%

Expecting the Unexpected: Predicting Panic Attacks from Mood and Twitter

McGinnis

Lunna

Berman

et al. 2023

Preprint

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Background: Panic attacks are an impairing mental health problem that affects about one in 10 US adults every year. Current DSM criteria describe panic attacks as unexpected, occurring without warning or triggering events. The unexpected nature of panic attacks not only leads to increased anxiety for the individual but has also made panic attacks particularly challenging to study. However, recent evidence suggests that individuals who experience such attacks could identify attack triggers. Objective: We aimed to explore both retrospectively and prospectively, qualitative, and quantitative factors associated with the onset of panic attacks. Method: We remotely recruited a diverse sample of 87 individuals who regularly experienced panic attacks from 30 states in the US. Participants responded to daily questions relating to their panic attacks and wellness behaviors each day for 28 days. We also considered daily community level factors captured by the Hedonometer, a metric which estimates population-level happiness daily using a random 10% of all public tweets. Results: Consistent with our prior work, most participants (95%) were able to retrospectively identify a trigger for their attack. Worse individual mood was associated with greater likelihood of experiencing a same-day panic attack over and above other individual wellness factors. Worse individually reported mood and state-based population level mood as indicated by the Hedonometer were associated with greater likelihood of next-day panic attack. Conclusions: These promising results suggest that individuals who experience panic attacks may be able to expect the unexpected. The importance of individual and state-based population level mood in panic attack risk could be used to ultimately inform future prevention and intervention efforts.

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Section: Discussionsupporting

confidence: 89%

Expecting the Unexpected: Predicting Panic Attacks from Mood and Twitter

McGinnis

Lunna

Berman

et al. 2023

Preprint

Self Cite

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“…Hedonometer scores derived from all English-language Tweets did not reach significance. This may suggest that proximity to the event moderates the strength of the association between societallevel mood and panic attacks, consistent with previous literature [13], [14], [28] which may be especially strong in highly anxious individuals [29], [30]. Psychoeducation on why and how panic attacks occur has been shown to be an effective intervention at least short-term [31], [32], and thus adding these results to psychoeducation may increase that benefit.…”

Section: Quantitative Panic Attack Triggerssupporting

confidence: 86%

Expecting the Unexpected: Predicting Panic Attacks From Mood, Twitter, and Apple Watch Data

McGinnis,

Loftness,

Lunna

et al. 2024

IEEE Open J. Eng. Med. Biol.

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Objective: Panic attacks are an impairing mental health problem that affects 11% of adults every year. Current criteria describe them as occurring without warning, despite evidence suggesting individuals can often identify attack triggers. We aimed to prospectively explore qualitative and quantitative factors associated with the onset of panic attacks. Results: Of 87 participants, 95% retrospectively identified a trigger for their panic attacks. Worse individually reported mood and state-level mood, as indicated by Twitter ratings, were related to greater likelihood of next-day panic attack. In a subsample of participants who uploaded their wearable sensor data (n = 32), louder ambient noise and higher resting heart rate were related to greater likelihood of next-day panic attack. Conclusions: These promising results suggest that individuals who experience panic attacks may be able to anticipate their next attack which could be used to inform future prevention and intervention efforts.

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“…The digital evolution of the occupy wall street movement was also widely investigated [72], highlighting a high degree of information localization key in resource mobilization [73]. In the last few years, further work has focused on the 'Me too' movement [74] and on online racial justice activism [75,76]. Finally, recently a complexity science approach has been proposed by an interdisciplinary group of scholars to better understand democratic instability dynamics, offering policy recommendations to help re-stabilize current systems of representative democracy, such as increasing diversity [77].…”

Section: Collective Action For Representative Democracymentioning

confidence: 99%

Complex systems for the most vulnerable

et al. 2022

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In a rapidly changing world, facing an increasing number of socioeconomic, health and environmental crises, complexity science can help us to assess and quantify vulnerabilities, and to monitor and achieve the UN Sustainable Development Goals. In this Perspective, we provide three exemplary use cases where complexity science has shown its potential: poverty and socioeconomic inequalities, collective action for representative democracy, and computational epidemic modeling. We then review the challenges and limitations related to data, methods, capacity building, and, as a result, research operationalization. We finally conclude with some suggestions for future directions, urging the complex systems community to engage in applied and methodological research addressing the needs of the most vulnerable.

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Say Their Names: Resurgence in the collective attention toward Black victims of fatal police violence following the death of George Floyd

Cited by 5 publications

References 33 publications

Expecting the Unexpected: Predicting Panic Attacks from Mood and Twitter

Expecting the Unexpected: Predicting Panic Attacks from Mood and Twitter

Expecting the Unexpected: Predicting Panic Attacks From Mood, Twitter, and Apple Watch Data

Complex systems for the most vulnerable

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