Purpose: To investigate tweets about marijuana edibles for surveillance into the content of edibles-related tweets among individuals socially networking about this topic on Twitter.
Design: Cross-sectional analysis of tweets containing edible marijuana-related key words during 1 month.
Setting: Twitter.
Participants: Tweets sent during January 1 to 31, 2015.
Methods: A random sample of 5000 tweets containing edibles-related key words was coded for sentiment (positive, negative, and neutral) by crowdsourced workers. Tweets normalizing or promoting edibles use were further analyzed, and demographic characteristics of the Twitter handles sending these tweets were inferred.
Results: Of the 5000 tweets, 4166 (83%) were about marijuana edibles, and of those 75% (3134 of 4166) normalized or encouraged edibles use. Nearly half (48%, 1509 of 3134) of the tweets normalizing edibles mentioned wanting or planning to consume, currently consuming, or recently consuming edibles, and 12% (378 of 3134) described the intense or long-lasting effects following use. Individuals whose tweets promoted/encouraged edibles use were more likely to be young (between 17 and 24 years old) and of a racial/ethnic minority (52% black; 12% Hispanic) when compared to the Twitter average.
Conclusion: Tweets that normalize edibles use have the potential to increase their popularity. The prevalence of tweets about edibles' intense high could have implications for tailoring prevention messages that could be important for youth and young adult minorities who were inferred to be disproportionately socially networking about edibles on Twitter.
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http://dx.doi.org/10.1177/0890117116686574 | DOI Listing |
PLoS One
January 2025
Computational Media Lab, University of Texas at Austin, Austin, Texas, United States of America.
Instead of turning to emergency phone systems, social media platforms, such as Twitter, have emerged as alternative and sometimes preferred venues for members of the public in the US to communicate during hurricanes and other natural disasters. However, relevant posts are likely to be missed by responders given the volume of content on platforms. Previous work successfully identified relevant posts through machine-learned methods, but depended on human annotators.
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January 2025
Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China.
With the advancement of the Internet, social media platforms have gradually become powerful in spreading crisis-related content. Identifying informative tweets associated with natural disasters is beneficial for the rescue operation. When faced with massive text data, choosing the pivotal features, reducing the calculation expense, and increasing the model classification performance is a significant challenge.
View Article and Find Full Text PDFCureus
December 2024
Department of Civil Engineering, Mepco Schlenk Engineering College, Sivakasi, IND.
Background Understanding the attitudes and perceptions of the general population is necessary for organizing health promotion initiatives. During outbreaks, social media has a significant impact on creating social perceptions. This study aims to identify and examine the emotions expressed and topics of discussion among Indian citizens related to COVID-19 third wave, from the messages posted on Twitter using text mining techniques.
View Article and Find Full Text PDFSoft comput
August 2024
Department of Computer Engineering, Suleyman Demirel University, Isparta, Turkey.
[This retracts the article DOI: 10.1007/s00500-022-06940-0.].
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January 2025
Centre for Postgraduate Studies, Cape Peninsula University of Technology, Cape Town, South Africa.
Big Data communication researchers have highlighted the need for qualitative analysis of online science conversations to better understand their meaning. However, a scholarly gap exists in exploring how qualitative methods can be applied to small data regarding micro-bloggers' communications about science articles. While social media attention assists with article dissemination, qualitative research into the associated microblogging practices remains limited.
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