Mining Social Media Data for Biomedical Signals and Health-Related Behavior

Correia, Rion Brattig; Wood, Ian B.; Bollen, Johan; Rocha, Luís M.

doi:10.1146/annurev-biodatasci-030320-040844

Cited by 53 publications

(59 citation statements)

References 152 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some examples include comparing the happiness of users to their online social networks [9,10], identifying detailed predictors of mood through social media feeds [5], predicting cognitive distortions expressed among groups at risk of mental health disorders [11], tracking the emotions of social media users at high resolution [12,13], and mapping negative affectivity among users with internalizing disorders [14]. Collectively, these studies demonstrate the feasibility and value of using sentiment analysis on social media data to study societal mood and well-being, as well as biomedical signals among social media users that can provide useful proxies for mental health [12,[15][16][17]. In fact, these approaches may be especially useful considering the speed that the pandemic became an acute socioeconomic phenomenon, the pervasiveness of COVID-19-related content available online, and the natural reaction of many to post on social media about pandemic-related events.…”

Section: Introductionmentioning

confidence: 99%

Social Media Insights Into US Mental Health During the COVID-19 Pandemic: Longitudinal Analysis of Twitter Data

Valdez¹,

Thij²,

Bathina³

et al. 2020

J Med Internet Res

Self Cite

226

151

View full text Add to dashboard Cite

Background The COVID-19 pandemic led to unprecedented mitigation efforts that disrupted the daily lives of millions. Beyond the general health repercussions of the pandemic itself, these measures also present a challenge to the world’s mental health and health care systems. Considering that traditional survey methods are time-consuming and expensive, we need timely and proactive data sources to respond to the rapidly evolving effects of health policy on our population’s mental health. Many people in the United States now use social media platforms such as Twitter to express the most minute details of their daily lives and social relations. This behavior is expected to increase during the COVID-19 pandemic, rendering social media data a rich field to understand personal well-being. Objective This study aims to answer three research questions: (1) What themes emerge from a corpus of US tweets about COVID-19? (2) To what extent did social media use increase during the onset of the COVID-19 pandemic? and (3) Does sentiment change in response to the COVID-19 pandemic? Methods We analyzed 86,581,237 public domain English language US tweets collected from an open-access public repository in three steps. First, we characterized the evolution of hashtags over time using latent Dirichlet allocation (LDA) topic modeling. Second, we increased the granularity of this analysis by downloading Twitter timelines of a large cohort of individuals (n=354,738) in 20 major US cities to assess changes in social media use. Finally, using this timeline data, we examined collective shifts in public mood in relation to evolving pandemic news cycles by analyzing the average daily sentiment of all timeline tweets with the Valence Aware Dictionary and Sentiment Reasoner (VADER) tool. Results LDA topics generated in the early months of the data set corresponded to major COVID-19–specific events. However, as state and municipal governments began issuing stay-at-home orders, latent themes shifted toward US-related lifestyle changes rather than global pandemic-related events. Social media volume also increased significantly, peaking during stay-at-home mandates. Finally, VADER sentiment analysis scores of user timelines were initially high and stable but decreased significantly, and continuously, by late March. Conclusions Our findings underscore the negative effects of the pandemic on overall population sentiment. Increased use rates suggest that, for some, social media may be a coping mechanism to combat feelings of isolation related to long-term social distancing. However, in light of the documented negative effect of heavy social media use on mental health, social media may further exacerbate negative feelings in the long-term for many individuals. Thus, considering the overburdened US mental health care structure, these findings have important implications for ongoing mitigation efforts.

show abstract

Section: Introductionmentioning

confidence: 99%

Social Media Insights Into US Mental Health During the COVID-19 Pandemic: Longitudinal Analysis of Twitter Data

Valdez¹,

Thij²,

Bathina³

et al. 2020

J Med Internet Res

Self Cite

226

151

View full text Add to dashboard Cite

show abstract

“…They may also be comfortable discussing sensitive personal concerns that they may not report to clinicians or researchers. In addition, online forums can be used to gather data from a large number of patients more quickly and inexpensively than a study that requires patient recruitment [21,22,34].…”

Section: Discussionmentioning

confidence: 99%

“…The limitations of social media data should also be acknowledged [21,22,34]. In online forums, patients are identified by screen names (i.e., pseudonyms), and they do not typically provide personal identifying information.…”

Section: Discussionmentioning

confidence: 99%

Qualitative Thematic Analysis of Social Media Data to Assess Perceptions of Route of Administration for Antiretroviral Treatment among People Living with HIV

Matza

Paulus

Garris

et al. 2020

Patient

View full text Add to dashboard Cite

Background HIV is a condition that requires lifelong treatment. Treatment options currently consist of oral antiretroviral therapies (ART) taken once or twice daily. Long-acting injectable HIV treatments are currently in development to be administered monthly or every other month. Preferences for route of administration could influence treatment adherence, which could affect treatment outcomes. The purpose of this study was to examine patient perceptions of oral and injectable routes of administration for ART. Methods Qualitative thematic analysis was conducted to examine 5122 online discussion threads by people living with HIV (PLHIV) in the POZ Community Forums from January 2013 to June 2018. Analysis focused on identifying perceptions of oral or injectable routes of administration for ART. Relevant threads were extracted and imported into the qualitative data analysis software package ATLAS.ti.8 so that text could be reviewed and coded. Results Analyses identified 684 relevant discussion threads including 2626 coded quotations from online posts by 568 PLHIV. The oral route of administration was discussed more frequently than injectable (2516 quotations for oral; 110 injectable). Positive statements on the oral route of administration commonly mentioned the small number of pills (276 quotations), dose frequency (245), ease of scheduling (153), and ease of use (146). PLHIV also noted disadvantages of the oral route of administration including negative emotional impact (166), difficulty with medication access (106), scheduling (131), and treatment adherence (121). Among the smaller number of PLHIV discussing injectable ART, common positive comments focused on dose frequency (34), emotional benefits of not taking a daily pill (7), potential benefits for adherence (6), overall convenience (6), and benefits for traveling (6). Some comments from PLHIV perceived the frequency of injections negatively (10), and others had negative perceptions of needles (8) or appointments required to receive injections (7). Conclusions Qualitative analysis revealed that route of administration was frequently discussed among PLHIV on this online forum. While many expressed positive views about their daily oral medication regimen, others perceived inconveniences and challenges. Among PLHIV who were aware of a possible monthly injectable treatment, many viewed this new route of administration as a convenient alternative with potential to improve adherence.

show abstract

“…While this could be any corpus of data, we suggest two here that may be of particular interest to health researchers and practitioners: social media about emerging health issues and scientific literature. Two features of social media posts make them appealing as a data source: (1) Individuals' posts are generally spontaneous and unprompted, naturally reducing biasing effects of survey instruments, and (2) social media posts occur in real-time, and do not incur lag time, which may detract from data during rapidly evolving events, such as natural disasters (Correia et al, 2020). See, for example, a study on crisis communication during Japan's 2011 earthquake (Cho et al, 2013).…”

Section: Future Usementioning

confidence: 99%

On Mining Words: The Utility of Topic Models in Health Education Research and Practice

Valdez

Picket

Young

et al. 2021

Health Promotion Practice

View full text Add to dashboard Cite

Written language is the primary means by which scientific research findings are disseminated. Yet in the era of information overload, dissemination of a field of research may require additional efforts given the sheer volume of material available on any specific topic. Topic models are unsupervised natural language processing methods that analyze nonnumeric data (i.e., text data) in abundance. These tools aggregate, and make sense of, those data making them interpretable to interested audiences. In this perspective piece, we briefly describe topic models, including their purpose, function, and applicability for health education researchers and practitioners. We note how topic models can be applied in several contexts, including social media–based analyses, and mapping trends in scientific literature over time. As a tool for studying words, and patterns of words, topic models stand to improve our understanding of events prior and those occurring in the moment and help us look ahead into the future.

show abstract

Mining Social Media Data for Biomedical Signals and Health-Related Behavior

Cited by 53 publications

References 152 publications

Social Media Insights Into US Mental Health During the COVID-19 Pandemic: Longitudinal Analysis of Twitter Data

Social Media Insights Into US Mental Health During the COVID-19 Pandemic: Longitudinal Analysis of Twitter Data

Qualitative Thematic Analysis of Social Media Data to Assess Perceptions of Route of Administration for Antiretroviral Treatment among People Living with HIV

On Mining Words: The Utility of Topic Models in Health Education Research and Practice

Contact Info

Product

Resources

About