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Skip search results from other journals and go to results- 2 JMIR Pediatrics and Parenting
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To leverage the potential of social media data and overcome some barriers related to social media research, this paper describes a simple and systematic approach to extracting qualitative data from a social media platform. The methods outlined in this paper were used to extract data from Facebook for a study on maternal perspectives on sudden unexpected infant death (SUID).
JMIR Form Res 2024;8:e54407
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Photos Shared on Facebook in the Context of Safe Sleep Recommendations: Content Analysis of Images
These included (1) a supine sleep position, (2) no bed sharing, (3) the absence of soft bedding (crib bumpers, positioners), (4) a safe sleep surface, and (5) pacifier use [3]. If there was a discrepancy in assessing the safety of the environment, this was discussed among the members until a consensus was reached.
JMIR Pediatr Parent 2024;7:e54610
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The post that received the most likes (n=20) was a Seattle Times article about a doctor who linked hearing dysfunction to SIDS; if infants failed the screening, they would undergo a more thorough exam because they were more at risk than those who passed. The post that received the second highest number of likes (n=12) was a post from a mother who wanted to know who else “went against the recommendations” and let their babies sleep prone.
J Med Internet Res 2020;22(7):e18474
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The first step was to extract, clean, and create a dictionary of words using a natural language processor. Using a Text Parsing node, each message was divided into individual words; these words were listed in a frequency matrix, and words that contributed little to the understanding of the topic, such as auxiliary verbs, conjunctions, determiners, interjections, participles, prepositions, and pronouns, were excluded from the analysis.
JMIR Pediatr Parent 2018;1(2):e10435
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