FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3097145486> ?p ?o ?g. }

• W3097145486 endingPage "e21660" @default.
• W3097145486 startingPage "e21660" @default.
• W3097145486 abstract "Background Modifiable risky health behaviors, such as tobacco use, excessive alcohol use, being overweight, lack of physical activity, and unhealthy eating habits, are some of the major factors for developing chronic health conditions. Social media platforms have become indispensable means of communication in the digital era. They provide an opportunity for individuals to express themselves, as well as share their health-related concerns with peers and health care providers, with respect to risky behaviors. Such peer interactions can be utilized as valuable data sources to better understand inter-and intrapersonal psychosocial mediators and the mechanisms of social influence that drive behavior change. Objective The objective of this review is to summarize computational and quantitative techniques facilitating the analysis of data generated through peer interactions pertaining to risky health behaviors on social media platforms. Methods We performed a systematic review of the literature in September 2020 by searching three databases—PubMed, Web of Science, and Scopus—using relevant keywords, such as “social media,” “online health communities,” “machine learning,” “data mining,” etc. The reporting of the studies was directed by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Two reviewers independently assessed the eligibility of studies based on the inclusion and exclusion criteria. We extracted the required information from the selected studies. Results The initial search returned a total of 1554 studies, and after careful analysis of titles, abstracts, and full texts, a total of 64 studies were included in this review. We extracted the following key characteristics from all of the studies: social media platform used for conducting the study, risky health behavior studied, the number of posts analyzed, study focus, key methodological functions and tools used for data analysis, evaluation metrics used, and summary of the key findings. The most commonly used social media platform was Twitter, followed by Facebook, QuitNet, and Reddit. The most commonly studied risky health behavior was nicotine use, followed by drug or substance abuse and alcohol use. Various supervised and unsupervised machine learning approaches were used for analyzing textual data generated from online peer interactions. Few studies utilized deep learning methods for analyzing textual data as well as image or video data. Social network analysis was also performed, as reported in some studies. Conclusions Our review consolidates the methodological underpinnings for analyzing risky health behaviors and has enhanced our understanding of how social media can be leveraged for nuanced behavioral modeling and representation. The knowledge gained from our review can serve as a foundational component for the development of persuasive health communication and effective behavior modification technologies aimed at the individual and population levels." @default.
• W3097145486 created "2020-11-09" @default.
• W3097145486 creator A5025538834 @default.
• W3097145486 creator A5045897236 @default.
• W3097145486 creator A5046709245 @default.
• W3097145486 creator A5055827526 @default.
• W3097145486 creator A5058224302 @default.
• W3097145486 creator A5071178113 @default.
• W3097145486 creator A5081331386 @default.
• W3097145486 date "2020-11-30" @default.
• W3097145486 modified "2023-09-30" @default.
• W3097145486 title "Social Media as a Research Tool (SMaaRT) for Risky Behavior Analytics: Methodological Review" @default.
• W3097145486 cites W1546447215 @default.
• W3097145486 cites W1795134912 @default.
• W3097145486 cites W1984926150 @default.
• W3097145486 cites W1988023854 @default.
• W3097145486 cites W2002851739 @default.
• W3097145486 cites W2032927944 @default.
• W3097145486 cites W2042506773 @default.
• W3097145486 cites W2057181385 @default.
• W3097145486 cites W2077780333 @default.
• W3097145486 cites W2086310388 @default.
• W3097145486 cites W2086763119 @default.
• W3097145486 cites W2086869155 @default.
• W3097145486 cites W2088481526 @default.
• W3097145486 cites W2091816755 @default.
• W3097145486 cites W2111896942 @default.
• W3097145486 cites W2117239687 @default.
• W3097145486 cites W2122700930 @default.
• W3097145486 cites W2122897171 @default.
• W3097145486 cites W2124280114 @default.
• W3097145486 cites W2125910575 @default.
• W3097145486 cites W2128000797 @default.
• W3097145486 cites W2130363090 @default.
• W3097145486 cites W2131263486 @default.
• W3097145486 cites W2134097264 @default.
• W3097145486 cites W2140910804 @default.
• W3097145486 cites W2141161236 @default.
• W3097145486 cites W2141249644 @default.
• W3097145486 cites W2142912849 @default.
• W3097145486 cites W2144928420 @default.
• W3097145486 cites W2147073231 @default.
• W3097145486 cites W2154013831 @default.
• W3097145486 cites W2154245896 @default.
• W3097145486 cites W2155002669 @default.
• W3097145486 cites W2168812176 @default.
• W3097145486 cites W2181648123 @default.
• W3097145486 cites W2224826979 @default.
• W3097145486 cites W2287695441 @default.
• W3097145486 cites W2293935477 @default.
• W3097145486 cites W2297673140 @default.
• W3097145486 cites W2300475701 @default.
• W3097145486 cites W2326456864 @default.
• W3097145486 cites W2330491661 @default.
• W3097145486 cites W2474187140 @default.
• W3097145486 cites W2514038762 @default.
• W3097145486 cites W2517785654 @default.
• W3097145486 cites W2527994330 @default.
• W3097145486 cites W2532655604 @default.
• W3097145486 cites W2536458098 @default.
• W3097145486 cites W2564368681 @default.
• W3097145486 cites W2571788821 @default.
• W3097145486 cites W2588382500 @default.
• W3097145486 cites W2592794011 @default.
• W3097145486 cites W2602928768 @default.
• W3097145486 cites W2606767616 @default.
• W3097145486 cites W2724146920 @default.
• W3097145486 cites W2738102631 @default.
• W3097145486 cites W2742715160 @default.
• W3097145486 cites W2743898363 @default.
• W3097145486 cites W2757878657 @default.
• W3097145486 cites W2759302549 @default.
• W3097145486 cites W2765672741 @default.
• W3097145486 cites W2766654852 @default.
• W3097145486 cites W2767551651 @default.
• W3097145486 cites W2774000474 @default.
• W3097145486 cites W2779695185 @default.
• W3097145486 cites W2788936360 @default.
• W3097145486 cites W2790362896 @default.
• W3097145486 cites W2794306471 @default.
• W3097145486 cites W2800564350 @default.
• W3097145486 cites W2801519849 @default.
• W3097145486 cites W2801922514 @default.
• W3097145486 cites W2807841350 @default.
• W3097145486 cites W2808707317 @default.
• W3097145486 cites W2841774036 @default.
• W3097145486 cites W2890481100 @default.
• W3097145486 cites W2895763047 @default.
• W3097145486 cites W2896691369 @default.
• W3097145486 cites W2897630147 @default.
• W3097145486 cites W2898548574 @default.
• W3097145486 cites W2898894513 @default.
• W3097145486 cites W2899170277 @default.
• W3097145486 cites W2900471836 @default.
• W3097145486 cites W2901945509 @default.
• W3097145486 cites W2937687852 @default.
• W3097145486 cites W2940156422 @default.
• W3097145486 cites W2945384117 @default.

• next