Background: "Rosin tech" is an emerging solventless method consisting in applying moderate heat and constant pressure on marijuana flowers to prepare marijuana concentrates referred to as "rosin." This paper explores rosin concentrate-related Twitter data to describe tweet content and analyze differences in rosin-related tweeting across states with varying cannabis legal statuses.
Method: English language tweets were collected between March 15, 2015 and April 17, 2017, using Twitter API. U.S. geolocated unique (no retweets) tweets were manually coded to evaluate the content of rosin-related tweets. Adjusted proportions of Twitter users and personal communication tweets per state related to rosin concentrates were calculated. A permutation test was used to analyze differences in normalized proportions between U.S. states with different cannabis legal statuses.
Results: eDrugTrends collected 8389 tweets mentioning rosin concentrates/technique. 4164 tweets (49.6% of total sample) posted by 1264 unique users had identifiable state-level geolocation. Content analysis of 2010 non-retweeted tweets revealed a high proportion of media-related tweets (44.2%) promoting rosin as a safer and solventless production method. Tweet-volume-adjusted percentages of geolocated Twitter users and personal communication tweets about rosin were respectively up to seven and sixteen times higher between states allowing recreational use of cannabis and states where cannabis is illegal.
Conclusion: Our results indicate that there are higher proportions of personal communication tweets and Twitter users tweeting about rosin in U.S. states where cannabis is legalized. Rosin concentrates are advertised as a safer, more natural form of concentrates, but more research on this emerging form of marijuana concentrate is needed.
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http://dx.doi.org/10.1016/j.drugalcdep.2017.10.039 | DOI Listing |
PLoS One
December 2024
Institute of Industrial Science, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.
To prevent widespread epidemics such as influenza or measles, it is crucial to reach a broad acceptance of vaccinations while addressing vaccine hesitancy and refusal. To gain a deeper understanding of Japan's sharp increase in COVID-19 vaccination coverage, we performed an analysis on the posts of Twitter users to investigate the formation of users' stances toward COVID-19 vaccines and information-sharing actions through the formation. We constructed a dataset of all Japanese posts mentioning vaccines for five months since the beginning of the vaccination campaign in Japan and carried out a stance detection task for all the users who wrote the posts by training an original deep neural network.
View Article and Find Full Text PDFFront Public Health
December 2024
Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Objective: To characterize the public conversations around long COVID, as expressed through X (formerly Twitter) posts from May 2020 to April 2023.
Methods: Using X as the data source, we extracted tweets containing #long-covid, #long_covid, or "long covid," posted from May 2020 to April 2023. We then conducted an unsupervised deep learning analysis using Bidirectional Encoder Representations from Transformers (BERT).
Sci Rep
December 2024
School of Statistics and Mathematics, Inner Mongolia University of Finance and Economics, Hohhot, 010070, China.
The propagation of public opinion in multilingual environments presents unique challenges due to the diversity of languages, cultures, and values. This study develops an SEIR-based model tailored for multilingual contexts, incorporating mechanisms such as social enhancement, forgetting, and cross-transmission. The model's purpose is to improve transparency, inclusivity, and effectiveness in public opinion management, particularly in diverse linguistic settings.
View Article and Find Full Text PDFJ Adolesc Young Adult Oncol
December 2024
Department of Human Development and Family Sciences, University of Connecticut, Storrs, Connecticut, USA.
Over a half million children are living with cancer in the United States. Social media platforms offer unique opportunities for cancer communication by public health organizations as well as health care providers, scientists, patients, and caregivers. Given the dearth of research on childhood cancer communication, the present study aimed to examine the nature of tweets on the social media platform X (formerly Twitter) that used the hashtag #childhoodcancer, the types of these tweets that attracted the most retweets, the types of users tweeting about childhood cancer (e.
View Article and Find Full Text PDFPLoS One
December 2024
SGH Warsaw School of Economics, Warsaw, Poland.
The study examines different graph-based methods of detecting anomalous activities on digital markets, proposing the most efficient way to increase market actors' protection and reduce information asymmetry. Anomalies are defined below as both bots and fraudulent users (who can be both bots and real people). Methods are compared against each other, and state-of-the-art results from the literature and a new algorithm is proposed.
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