Dataset Information

Learning from social media: utilizing advanced data extraction techniques to understand barriers to breast cancer treatment.

ABSTRACT: Past examinations of breast cancer treatment barriers have typically included registry, claims-based, and smaller survey studies. We examined treatment barriers using a novel, comprehensive, social media analysis of online, candid discussions about breast cancer. Using an innovative toolset to search postings on social networks, message boards, patient communities, and topical sites, we performed a large-scale qualitative analysis. We examined the sentiments and barriers expressed about breast cancer treatments by Internet users during 1 year (2/1/14-1/31/15). We categorized posts based on thematic patterns and examined trends in discussions by race/ethnicity (white/black/Hispanic) when this information was available. We identified 1,024,041 unique posts related to breast cancer treatment. Overall, 57 % of posts expressed negative sentiments. Using machine learning software, we assigned treatment barriers for 387,238 posts (38 %). Barriers included emotional (23 % of posts), preferences and spiritual/religious beliefs (21 %), physical (18 %), resource (15 %), healthcare perceptions (9 %), treatment processes/duration (7 %), and relationships (7 %). Black and Hispanic (vs. white) users more frequently reported barriers related to healthcare perceptions, beliefs, and pre-diagnosis/diagnosis organizational challenges and fewer emotional barriers. Using a novel analysis of diverse social media users, we observed numerous breast cancer treatment barriers that differed by race/ethnicity. Social media is a powerful tool, allowing use of real-world data for qualitative research, capitalizing on the rich discussions occurring spontaneously online. Future research should focus on how to further employ and learn from this type of social intelligence research across all medical disciplines.

SUBMITTER: Freedman RA

PROVIDER: S-EPMC5537590 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Learning from social media: utilizing advanced data extraction techniques to understand barriers to breast cancer treatment.

Freedman Rachel A RA Viswanath Kasisomayajula K Vaz-Luis Ines I Keating Nancy L NL

Breast cancer research and treatment 20160623 2

Past examinations of breast cancer treatment barriers have typically included registry, claims-based, and smaller survey studies. We examined treatment barriers using a novel, comprehensive, social media analysis of online, candid discussions about breast cancer. Using an innovative toolset to search postings on social networks, message boards, patient communities, and topical sites, we performed a large-scale qualitative analysis. We examined the sentiments and barriers expressed about breast c ...[more]

PMID: 27339067

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Project description:BackgroundHazardous drinking among college students persists, despite ongoing university alcohol education and alcohol intervention programs. College students often post comments or pictures of drinking episodes on social media platforms.ObjectiveThis study aimed to understand one university's student attitudes toward alcohol use by examining student posts about drinking on social media platforms and to identify opportunities to reduce alcohol-related harm and inform novel alcohol interventions.MethodsWe analyzed social media posts from 7 social media platforms using qualitative inductive coding based on grounded theory to identify the contexts of student drinking and the attitudes and behaviors of students and peers during drinking episodes. We reviewed publicly available social media posts that referenced alcohol, collaborating with undergraduate students to select their most used platforms and develop locally relevant search terms; all posts in our data set were generated by students associated with a specific university. From the codes, we derived themes about student culture regarding alcohol use.ResultsIn total, 1151 social media posts were included in this study. These included 809 Twitter tweets, 113 Instagram posts, 100 Greekrank posts, 64 Reddit posts, 34 College Confidential posts, 23 Facebook posts, and 8 YouTube posts. Posts included both implicit and explicit portrayals of alcohol use. Across all types of posts reviewed, positive drinking attitudes were most common, followed by negative and then neutral attitudes, but valence varied by platform. Posts that portrayed drinking positively received positive peer feedback and indicate that drinking is viewed by students as an essential and positive part of university student culture.ConclusionsSocial media provide a real-time picture of students' behavior during their own and others' heavy drinking. Posts portray heavy drinking as a normal part of student culture, reinforced by peers' positive feedback on posts. Interventions for college drinking should help students manage alcohol intake in real time, provide safety information during alcohol use episodes, and raise student awareness of web-based privacy concerns and reputation management. Additional interventions for students, alumni, and parents are needed to address positive attitudes about and traditions of drinking.

Dataset Information

Learning from social media: utilizing advanced data extraction techniques to understand barriers to breast cancer treatment.

Publications

Learning from social media: utilizing advanced data extraction techniques to understand barriers to breast cancer treatment.

Similar Datasets

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