Researchers and policy makers worldwide are interested in measuring the subjective well-being of populations. When users post on social media, they leave behind digital traces that reflect their thoughts feelings. Aggregation such may make it possible to monitor at large scale. However, media-based methods need be robust regional effects if produce reliable estimates. Using a sample 1.53 billion geotagged English tweets, we provide systematic evaluation word-level data-driven for text...

On May 25, 2020, George Floyd, an unarmed Black American male, was killed by a White police officer. Footage of the murder widely shared. We examined psychological impact Floyd's death using two population surveys that collected data before and after his death; one from Gallup (117,568 responses n = 47,355) US Census (409,652 319,471). According to data, in week following death, anger sadness increased unprecedented levels population. During this period, more than third reported these...

As of March 2021, the SARS-CoV-2 virus has been responsible for over 115 million cases COVID-19 worldwide, resulting in 2.5 deaths. spread exponentially, so did its media coverage, a proliferation conflicting information on social platforms-a so-called "infodemic." In this viewpoint, we survey past literature investigating role automated accounts, or "bots," spreading such misinformation, drawing connections to pandemic. We also review strategies used by bots (mis)information and examine...

H. Andrew Schwartz, Salvatore Giorgi, Maarten Sap, Patrick Crutchley, Lyle Ungar, Johannes Eichstaedt. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. 2017.

Beck's insight-that beliefs about one's self, future, and environment shape behavior-transformed depression treatment. Yet remain relatively understudied. We introduce a set of beliefs-primal world or primals-that concern the world's overall character (e.g., is interesting, dangerous). To create measure, we systematically identified candidate primals analyzing tweets, historical texts, etc.); conducted exploratory factor analysis (N = 930) two confirmatory analyses 524; N 529); examined...

Objectives The current study analyzes a large set of Twitter data from 1,384 US counties to determine whether excessive alcohol consumption rates can be predicted by the words being posted each county. Methods Data over 138 million county-level tweets were analyzed using predictive modeling, differential language analysis, and mediating analysis. Results captures cross-sectional patterns beyond that sociodemographic factors (e.g. age, gender, race, income, education), used accurately predict...

The language that individuals use for expressing themselves contains rich psychological information. Recent significant advances in Natural Language Processing (NLP) and Deep Learning (DL), namely transformers, have resulted large performance gains tasks related to understanding natural language. However, these state-of-the-art methods not yet been made easily accessible psychology researchers, nor designed be optimal human-level analyses. This tutorial introduces text (https://r-text.org/),...

Depression has robust natural language correlates and can increasingly be measured in using predictive models. However, despite evidence that use varies as a function of individual demographic features (e.g., age, gender), previous work not systematically examined whether how depression's association with by race. We examine race moderates the relationship between (i.e., first-person pronouns negative emotions) from social media posts self-reported depression, matched sample Black White...

Abstract In the most comprehensive population surveys, mental health is only broadly captured through questionnaires asking about “mentally unhealthy days” or feelings of “sadness.” Further, estimates are predominantly consolidated to yearly at state level, which considerably coarser than best physical health. Through large-scale analysis social media, robust estimation feasible finer resolutions. this study, we created a pipeline that used ~1 billion Tweets from 2 million geo-located users...

Research into the darker traits of human nature is growing in interest especially context increased social media usage. This allows users to express themselves a wider online audience. We study extent which standard model dark personality -- triad consisting narcissism, psychopathy and Machiavellianism, related observable Twitter behavior such as platform usage, posted text profile image choice. Our results show that we can map various behaviors psychological theory new aspects Finally,...

Lucie Flekova, Jordan Carpenter, Salvatore Giorgi, Lyle Ungar, Daniel Preoţiuc-Pietro. Proceedings of the 54th Annual Meeting Association for Computational Linguistics (Volume 1: Long Papers). 2016.

Abstract Aims This pilot study aimed to identify associations of loneliness and daily alcohol consumption among US adults during the Coronavirus Disease-2019 pandemic. Method Participants completed assessments for 30 days. Results suggest people who feel lonelier on average drink more alcohol, however, than usual less. Conclusion Findings highlight need disaggregate within- between-person components use.

Black Lives Matter (BLM) is a decentralized social movement protesting violence against individuals and communities, with focus on police brutality. The gained significant attention following the killings of Ahmaud Arbery, Breonna Taylor, George Floyd in 2020. #BlackLivesMatter media hashtag has come to represent grassroots movement, similar hashtags counter BLM such as #AllLivesMatter, #BlueLivesMatter. We introduce data set 63.9 million tweets from 13.0 users over 100 countries which...

Abstract Background & Aims Previous studies have shown that nonsuicidal self-injury (NSSI) has addictive features, and an addiction model of NSSI been considered. Addictive features associated with severity adverse psychological experiences. Yet, there is debate over the extent to which substance use disorders (SUDs) are similar experientially. Methods To evaluate people who self-injure experience like addiction, we coded posts users subreddit r/selfharm ( n = 500) for each 11 DSM-5 SUD...

This paper presents a framework for Virtual Open Laboratory Teaching Assistant (VOLTA) which provides personalized instructions undergraduate students in an entry level electrical circuits laboratory.Traditional closed laboratory environments do not provide 24/7 access to such labs hindering the learning-on-demand paradigm that is so critical experience.VOLTA offers open environment with virtual teaching assistant where enjoy self-paced learning increased of engagement.VOLTA short...

Mohammadzaman Zamani, H. Andrew Schwartz, Johannes Eichstaedt, Sharath Chandra Guntuku, Adithya Virinchipuram Ganesan, Sean Clouston, Salvatore Giorgi. Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science. 2020.

Technology now makes it possible to understand efficiently and at large scale how people use language reveal their everyday thoughts, behaviors, emotions. Written text has been analyzed through both theory-based, closed-vocabulary methods from the social sciences as well data-driven, open-vocabulary computer science, but these approaches have not comprehensively compared. To provide guidance on best practices for automatically analyzing written text, this narrative review quantitative...

The language that individuals use for expressing themselves contains rich psychological information. Recent significant advances in Natural Language Processing (NLP) and Deep Learning (DL), namely transformers, have resulted large performance gains tasks related to understanding natural language. However, these state-of-the-art methods not yet been made easily accessible psychology researchers, nor designed be optimal human-level analyses. This tutorial introduces text (https://r-text.org/),...

Research conducted during the COVID-19 Pandemic has identified two co-occurring public health concerns: loneliness and substance use. Findings from research prior to pandemic are inconclusive as links between This study aimed measure associations of with three different types use COVID-19: daily number alcoholic drinks, cannabis use, non-cannabis drug use.Data were obtained October 2020 May 2021 2,648 US adults (Mage = 38.76, 65.4% women) diverse respect race ethnicity using online...

Targeting of location-specific aid for the U.S. opioid epidemic is difficult due to our inability accurately predict changes in mortality across heterogeneous communities. AI-based language analyses, having recently shown promise cross-sectional (between-community) well-being assessments, may offer a way more longitudinally community-level overdose mortality. Here, we develop and evaluate, TROP (Transformer Opiod Prediction), model community-specific trend projection that uses social media...

Nowcasting based on social media text promises to provide unobtrusive and near real-time predictions of community-level outcomes. These outcomes are typically regarding people, but the data is often aggregated without regard users in Twitter populations each community. This paper describes a simple yet effective method for building models using language by user. Results four different U.S. county-level tasks, spanning demographic, health, psychological show large consistent improvements...