Using matched samples to estimate the effects of exercise on mental health from twitter

By Virgile Landeiro Dos Reis, Aron Culotta. 2015

54 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

You Can't Stay Here (2017, methodology): “Matching techniques have been used to create treatment and control groups of users in studies focusing on social phenomena such as online antisocial behavior [10], mental health [16], dietary choices [12], and weight loss [11].”
Distilling the Outcomes of Personal Experiences: A Propensity-scored Analysis of Social Media (2017, background): “In addition, observing the decisions of others can also explain various human phenomena such as when and why mass convergent behavior is prone to fads and errors, and can, thus, offer important insights to economists, policy-makers, and others [15, 28, 31].”
Emoticons vs. Emojis on Twitter: A Causal Inference Approach (2015, methodology): “tiﬁcation (Frangakis and Rubin 2002). There has been some recent work employing causal inference techniques such as matching in large scale quantitative studies using observational social media data (Reis and Culotta 2015; Cheng, Danescu-Niculescu-Mizil, and Leskovec 2015). We apply these approaches”
A Social Media Study on the Effects of Psychiatric Medication Use (2019, background): “…naturalistic patterns of mood, behavior, cognition, social milieu, and even mental and psychological states, both in real-time and longitudinally (Chancellor et al. 2016, Coppersmith et al. 2014, De Choudhury et al. 2013, Dos Reis and Culotta 2015, Saha et al. 2019a, Yoo and De Choudhury 2019).”
From ADHD to SAD: Analyzing the Language of Mental Health on Twitter through Self-Reported Diagnoses (2015, background): “Dos Reis and Culotta (2015) demonstrated that failing to account for these can yield biased control groups that skew results, so we aim to form approximate age- and gendermatched control groups.”