The Experts below are selected from a list of 71193 Experts worldwide ranked by ideXlab platform
Daniel Dajun Zeng - One of the best experts on this subject based on the ideXlab platform.
-
identifying topics for e cigarette user generated contents a case study from multiple social Media Platforms
Journal of Medical Internet Research, 2017Co-Authors: Yongcheng Zhan, Ruoran Liu, Scott J Leischow, Daniel Dajun ZengAbstract:Background: Electronic cigarette (e-cigarette) is an emerging product with a rapid-growth market in recent years. Social Media has become an important platform for information seeking and sharing. We aim to mine hidden topics from e-cigarette datasets collected from different social Media Platforms. Objective: This paper aims to gain a systematic understanding of the characteristics of various types of social Media, which will provide deep insights into how consumers and policy makers effectively use social Media to track e-cigarette-related content and adjust their decisions and policies. Methods: We collected data from Reddit (27,638 e-cigarette flavor-related posts from January 1, 2011, to June 30, 2015), JuiceDB (14,433 e-juice reviews from June 26, 2013 to November 12, 2015), and Twitter (13,356 “e-cig ban”-related tweets from January, 1, 2010 to June 30, 2015). Latent Dirichlet Allocation, a generative model for topic modeling, was used to analyze the topics from these data. Results: We found four types of topics across the Platforms: (1) promotions, (2) flavor discussions, (3) experience sharing, and (4) regulation debates. Promotions included sales from vendors to users, as well as trades among users. A total of 10.72% (2,962/27,638) of the posts from Reddit were related to trading. Promotion links were found between social Media Platforms. Most of the links (87.30%) in JuiceDB were related to Reddit posts. JuiceDB and Reddit identified consistent flavor categories. E-cigarette vaping methods and features such as steeping, throat hit, and vapor production were broadly discussed both on Reddit and on JuiceDB. Reddit provided space for policy discussions and majority of the posts (60.7%) holding a negative attitude toward regulations, whereas Twitter was used to launch campaigns using certain hashtags. Our findings are based on data across different Platforms. The topic distribution between Reddit and JuiceDB was significantly different (P<.001), which indicated that the user discussions focused on different perspectives across the Platforms. Conclusions: This study examined Reddit, JuiceDB, and Twitter as social Media data sources for e-cigarette research. These mined findings could be further used by other researchers and policy makers. By utilizing the automatic topic-modeling method, the proposed unified feedback model could be a useful tool for policy makers to comprehensively consider how to collect valuable feedback from social Media. [J Med Internet Res 2017;19(1):e24]
Everette A James - One of the best experts on this subject based on the ideXlab platform.
-
use of multiple social Media Platforms and symptoms of depression and anxiety
Computers in Human Behavior, 2017Co-Authors: Brian A Primack, Ariel Shensa, Csar G Escobarviera, Erica L Barrett, Jaime E Sidani, Jason B Colditz, Everette A JamesAbstract:IntroductionWhile increased time spent on social Media (TSSM) has been associated with depression and anxiety, the independent role of using multiple social Media (SM) Platforms is unclear. MethodsWe surveyed a nationally-representative sample of 1787 U.S. young adults ages 1932. Depression and anxiety symptoms were measured using the Patient-Reported Outcomes Measurement Information System (PROMIS). We assessed use of multiple SM Platforms with an adapted Pew Internet Research scale. We used ordered logistic regression models to assess associations between use of multiple SM Platforms and mental health outcomes while controlling for eight covariates, including overall TSSM. ResultsCompared to those who used 02 social Media Platforms, participants who used 711 social Media Platforms had substantially higher odds of having increased levels of both depression (Adjusted Odds Ratio [AOR]=3.0, 95% CI=1.94.8) and anxiety symptoms (AOR=3.2, 95% CI=2.05.1). Associations were linear (p<0.001 for all) and robust to all sensitivity analyses. ConclusionsUse of multiple SM Platforms is independently associated with symptoms of depression and anxiety, even when controlling for overall TSSM. These associations are strong enough that it may be valuable for clinicians to ask individuals with depression and anxiety about multiple platform use and to counsel regarding this potential contributing factor. We found a linear association between the number of Platforms used and depression.We found a linear association between the number of Platforms used and anxiety.Associations remained strong after controlling for total time of social Media use.
Brian A Primack - One of the best experts on this subject based on the ideXlab platform.
-
use of multiple social Media Platforms and symptoms of depression and anxiety
Computers in Human Behavior, 2017Co-Authors: Brian A Primack, Ariel Shensa, Csar G Escobarviera, Erica L Barrett, Jaime E Sidani, Jason B Colditz, Everette A JamesAbstract:IntroductionWhile increased time spent on social Media (TSSM) has been associated with depression and anxiety, the independent role of using multiple social Media (SM) Platforms is unclear. MethodsWe surveyed a nationally-representative sample of 1787 U.S. young adults ages 1932. Depression and anxiety symptoms were measured using the Patient-Reported Outcomes Measurement Information System (PROMIS). We assessed use of multiple SM Platforms with an adapted Pew Internet Research scale. We used ordered logistic regression models to assess associations between use of multiple SM Platforms and mental health outcomes while controlling for eight covariates, including overall TSSM. ResultsCompared to those who used 02 social Media Platforms, participants who used 711 social Media Platforms had substantially higher odds of having increased levels of both depression (Adjusted Odds Ratio [AOR]=3.0, 95% CI=1.94.8) and anxiety symptoms (AOR=3.2, 95% CI=2.05.1). Associations were linear (p<0.001 for all) and robust to all sensitivity analyses. ConclusionsUse of multiple SM Platforms is independently associated with symptoms of depression and anxiety, even when controlling for overall TSSM. These associations are strong enough that it may be valuable for clinicians to ask individuals with depression and anxiety about multiple platform use and to counsel regarding this potential contributing factor. We found a linear association between the number of Platforms used and depression.We found a linear association between the number of Platforms used and anxiety.Associations remained strong after controlling for total time of social Media use.
Bernard J Jansen - One of the best experts on this subject based on the ideXlab platform.
-
SocInfo - Predicting Audience Engagement Across Social Media Platforms in the News Domain
Lecture Notes in Computer Science, 2019Co-Authors: Kholoud Khalil Aldous, Bernard J JansenAbstract:We analyze cross-platform factors for posts on both single and multiple social Media Platforms for numerous news outlets to better predict audience engagement, precisely the number of likes and comments. We collect 676,779 social Media posts from 53 news outlets during eight months on four social Media Platforms (Facebook, Instagram, Twitter, and YouTube), along with the associated comments (more than 31 million) and the number of likes (more than 840 million). We develop a framework for predicting the audience engagement based on both linguistic features of the post and social Media platform factors. Among other findings, results show that content with high engagement on one platform does not guarantee high engagement on another platform, even when news outlets use similar cross-platform posts; however, for some content, cross-sharing posts on a platform will increase overall audience engagement on another platform. As one of the few multiple social Media platform studies, the findings have implications for the news domain, as well as other fields that distribute online content via social Media.
-
gen x and ys attitudes on using social Media Platforms for opinion sharing
Human Factors in Computing Systems, 2010Co-Authors: Bernard J Jansen, Kate Sobel, Geoff CookAbstract:In this paper, we investigate opinion sharing attitudes and behaviors of 13 - 24 year olds on social Media Platforms. This research utilizes data from 34,514 survey respondents from users of the social Media site, myYearbook. Results show that those more engaged with multiple social Media Platforms are more willing to share opinions, seek opinions, and act on these opinions. However, there were statistically significant differences among users of myYearbook, MySpace, Facebook, and Twitter. Findings show that the reported demographic differences and social network service chosen have an effect on behaviors. These results have implications for businesses and others interested in advertising on these Platforms, and researchers interested in investigating these populations.
Andrew Schorr - One of the best experts on this subject based on the ideXlab platform.
-
twitter 101 and beyond introduction to social Media Platforms available to practicing hematologist oncologists
Seminars in Hematology, 2017Co-Authors: Michael A Thompson, Jenny Ahlstrom, Don S Dizon, Yash Gad, Greg Dean Matthews, Howard J Luks, Andrew SchorrAbstract:Abstract Social Media utilizes specific Media Platforms to allow increased interactivity between participants. These Platforms serve diverse groups and purposes including participation from patients, family caregivers, research scientists, physicians, and pharmaceutical companies. Utilization of these information outlets has increased with integration at conferences and between conferences with the use of hashtags and “chats”. In the realm of the “e-Patient” it is key to not underestimate your audience. Highly technical information is just as useful as a basic post. With growing use, social Media analytics help track the volume and impact of content. Additionally, Platforms are leveraging each other for uses, including Twitter, blogs, web radio, and recorded video and images. We explore information on social Media resources and applications from varying perspectives. While these Platforms will evolve over time, or disappear with new Platforms taking their place, it is apparent they are now a part of the everyday experience of oncology communication.
