1 / 37

Online Social Dynamics and Well-being

Online Social Dynamics and Well-being. Munmun De Choudhury Assistant Professor, School of Interactive Computing, Georgia Tech March 12, 2014. Photo courtesy NPR. h ealth and wellness. affective disorders are a serious challenge in public health—statistics under-reported in large populations.

finley
Download Presentation

Online Social Dynamics and Well-being

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Online Social Dynamics and Well-being • Munmun De Choudhury • Assistant Professor, School of Interactive Computing, Georgia Tech • March 12, 2014

  2. Photo courtesy NPR

  3. health and wellness

  4. affective disorders are a serious challenge in public health—statistics under-reported in large populations

  5. Three problems

  6. Photo courtesy of NIDA.gov

  7. (De Choudhury, Counts, Horvitz, CSCW 2013a) Honorable Mention Award Research Question: • Examine patterns of activity and emotional correlates for childbirth and postnatal course leveraging activity in social media (Twitter)

  8. (De Choudhury, Counts, Horvitz, CSCW 2013a) Behavioral Changes of New Mothers Blue line represents approximate time of childbirth. The red line represents mothers and the green line represents the background cohort

  9. (De Choudhury, Counts, Horvitz, CSCW 2013a) Individual-level Comparison Certain mothers show more drastic change in behavioral measures than others

  10. (De Choudhury, Counts, Horvitz, CSCW 2013a) Language Differences percent of all unigrams in the language vocabulary used that changed significantly in usage frequency after childbirth, i.e. with p < .01 based on paired sample t-tests top unigrams showing the most change (in usage frequency) in the postnatal period, compared to the prenatal phase

  11. (De Choudhury, Counts, Horvitz, CSCW 2013a) Greedy Differencing Analysis • determine the number of unigrams whose change in usage frequencies renders the mothers with large effects significantly different • the deviations for certain new mothers captured by a rather small number of unigrams: • 1.16% compared to mothers with small effects • 10.73% with respect to the background cohort

  12. (De Choudhury, Counts, Horvitz, Hoff, CSCW 2014a) Facebook & Postpartum Depression • Web survey to recruit mothers who were Facebook users and who gave birth to a child within the last nine months or less • To incentivize participation, mothers were entered into the random drawing of four $500 Amazon gift cards • Survey was active between mid-July and mid-September, 2012 • Advertised through: • Mailing list of new mothers at Microsoft • Neighborhood based mommy blogs in the Seattle metro area • Postings from our organization’s official Twitter and Facebook accounts • Our personal Twitter, Facebook and Google+ accounts • Paid Facebook ads targeting mothers in the age group 20-39 years • Sponsored posts on BabyCenter (babycenter.com)

  13. (De Choudhury, Counts, Horvitz, Hoff, CSCW 2014a) • Patient Health Questionnaire (PHQ-9) • the 9-item questionnaire seeks responses over the past two week period • based directly on the nine diagnostic criteria for major depressive disorder in the DSM-IV (Diagnostic and Statistical Manual Fourth Edition) • scores on the PHQ-9 range from zero to 27; individuals with scores 15 or above are considered to be moderately severe to severely depressed (Kroenkeet al. 2001)

  14. (De Choudhury, Counts, Horvitz, Hoff, CSCW 2014a) Prediction Task • The prenatal period does provide PPD-predictive information together with a brief period of postnatal observations. • Aligns with findings in the clinical literature where prepartumdepression is known to be a good indicator of PPD(Beck 2001).

  15. (De Choudhury, Counts, Horvitz, CSCW 2013a) Honorable Mention Award Low-cost, privacy-preserving mechanisms to identify new mothers’ behavior can improve social support and encourage postpartum wellness

  16. (De Choudhury, Gamon, Counts, Horvitz, ICWSM 2013) Study Methodology • Ground truth data on clinical depression condition of 476 individuals was collected through a behavioral study • crowdsourcing (Mechanical Turk) driven methodology • use of the CES-D depression screening survey (Center for Epidemiologic Studies Depression Scale); an auxiliary screening test—Beck’s Depression Inventory was used to reduce noisy responses data collection methodology (twitter)

  17. (De Choudhury, Gamon, Counts, Horvitz, ICWSM 2013) Social media characteristics of MDD

  18. (De Choudhury, Gamon, Counts, Horvitz, ICWSM 2013) Depressive language use

  19. (De Choudhury, Gamon, Counts, Horvitz, ICWSM 2013) Predicting MDD • mean frequency—the average measure of the time series of a feature at any given day: µi=(1/N)∑tXi(t). • variance—the variation in the time series: (1/N)∑t(Xi(t) −µi)2. • mean momentum—relative trend of a time series, compared to a period before: (1/N)∑t(Xi(t)-(1/(t-M))∑(M≤k≤t-1)Xi(k)). • entropy—the measure of uncertainty in a time series: −∑tXi(t)log(Xi(t)).

  20. (De Choudhury, Counts, Horvitz, WebSci 2013) Social media depression index standardized difference between frequencies of depression-indicative and standard posts, compared to a period before between k and t-1 (1≤k≤t-1) actual (NIMH data) predicted (SMDI) least squares regression fit yields correlation of 0.52

  21. (De Choudhury, Counts, Horvitz, WebSci 2013)

  22. (De Choudhury, Monroy-Hernandez, Mark, CHI 2014) Best Paper Award The Atlantic

  23. (De Choudhury, Monroy-Hernandez, Mark, CHI 2014) A Case Study • The Mexican Drug War is an example of protracted trauma that has exposed people to persistent acts of violence. • Many Mexican cities affected • rapid increase of shootings and homicides, loss of life of innocent civilians. • increase of criminal activities such as extortions, and kidnappings • as of 2011, the Drug War had claimed 60,000 lives and had displaced between 230,000 and 1.6 million people. However unconfirmed reports set the homicide statistics over 100,000 victims (Booth, 2012)

  24. (De Choudhury, Monroy-Hernandez, Mark, CHI 2014) Challenges • As early as 2010, local health officials had reported a significant increase in the number of people seeking mental health help with post-traumatic stress disorder (PTSD) induced by drug-related violence (O’Connor, 2013). • The international news media have reported how Mexicans are “numb to carnage” (Archibold & Cave, 2012)and even kids are “exposed to such violence that they’re desensitized” (Hopewell, 2013).

  25. Goal: (De Choudhury, Monroy-Hernandez, Mark, CHI 2014) Study affective responses in social media and how they might indicate desensitization to violence experienced in communities embroiled in an armed conflict

  26. (De Choudhury, Monroy-Hernandez, Mark, CHI 2014) Negative Affect Towards the beginning of the time period of analysis, i.e., early on in 2010 or early 2011, the peaks in number of homicides are actually correlated with those in NA. However over time, especially in 2012, that ceases to be the case

  27. (De Choudhury, Monroy-Hernandez, Mark, CHI 2014) Activation, Dominance Over time, from the trends of activation, we observe a general increase, implying that Twitter users mentioning the four cities in their postings, were increasingly using higher intensity emotions. Dominance shows a rise with persistent violence (ref. the slope of the linear fit), indicating that users are increasingly using dominating and aggressive emotions

  28. borderlandbeat.com

  29. Thanks!Questions?mchoudhu@cc.gatech.edu@munmun10

More Related