scholarly journals #Crohns: historical cohort of Twitter activity

2020 ◽  
Author(s):  
Marcio Roberto Facanali Junior ◽  
Carolina Bortolozzo Graciolli Facanali ◽  
Natália Souza Freitas Queiroz ◽  
Carlos Walter Sobrado Junior ◽  
Sérgio Carlos Nahas ◽  
...  

Abstract Aim Analysis of the twitter activity on #Crohns, identifying individuals with interest in Crohn´s disease on Twitter. Methods A historic cohort study about Twitter activity evaluation of #Crohns, analyzed over a period of 9 years. For the twitter analysis, a health care social media analytics tool, Symplur Signals, was adopted. Results Since 2011 until 2019, 627.000 tweets of #Crohns were detected, with 276.380 retweets by 109.937 users, of these users 32.4% are patients advocate and 12.6% doctors. There was a pattern of annual peak activity of the #Crohns, mainly in May and December, and less activity, usually in July. Of all tweets, 52.5% were categorized as positive and 47.5% as negative. Conclusion Social media, especially Twitter, represents an important information tool, but it is still underutilized by gastroenterologists. This study suggests a significant interference of international awareness campaigns about IBD in the activity of #Crohns on Twitter, denoting an increase in debating this topic on the platform. Discussions on the subject by health professionals are still below expectations regarding the importance of the theme.

2014 ◽  
Vol 35 (1) ◽  
pp. 7-43 ◽  
Author(s):  
Dick M. Carpenter ◽  
Jenifer Walsh Robertson ◽  
Michele E. Johnson ◽  
Scott Blum

2020 ◽  
Author(s):  
Jay Palmer ◽  
Kyle Revis ◽  
Yves Romain

2021 ◽  
pp. 089443932110122
Author(s):  
Dennis Assenmacher ◽  
Derek Weber ◽  
Mike Preuss ◽  
André Calero Valdez ◽  
Alison Bradshaw ◽  
...  

Computational social science uses computational and statistical methods in order to evaluate social interaction. The public availability of data sets is thus a necessary precondition for reliable and replicable research. These data allow researchers to benchmark the computational methods they develop, test the generalizability of their findings, and build confidence in their results. When social media data are concerned, data sharing is often restricted for legal or privacy reasons, which makes the comparison of methods and the replicability of research results infeasible. Social media analytics research, consequently, faces an integrity crisis. How is it possible to create trust in computational or statistical analyses, when they cannot be validated by third parties? In this work, we explore this well-known, yet little discussed, problem for social media analytics. We investigate how this problem can be solved by looking at related computational research areas. Moreover, we propose and implement a prototype to address the problem in the form of a new evaluation framework that enables the comparison of algorithms without the need to exchange data directly, while maintaining flexibility for the algorithm design.


Author(s):  
Sebastian Zhi Tao Khoo ◽  
Leong Hock Ho ◽  
Ee Hong Lee ◽  
Danston Kheng Boon Goh ◽  
Zehao Zhang ◽  
...  

Author(s):  
Kathy McKay ◽  
Sarah Wayland ◽  
David Ferguson ◽  
Jane Petty ◽  
Eilis Kennedy

In the UK, tweets around COVID-19 and health care have primarily focused on the NHS. Recent research has identified that the psychological well-being of NHS staff has been adversely impacted as a result of the COVID-19 pandemic. The aim of this study was to investigate narratives relating to the NHS and COVID-19 during the first lockdown (26 March–4 July 2020). A total of 123,880 tweets were collated and downloaded bound to the time period of the first lockdown in order to analyse the real-time discourse around COVID-19 and the NHS. Content analysis was undertaken and tweets were coded to positive and negative sentiments. Five main themes were identified: (1) the dichotomies of ‘clap for carers’; (2) problems with PPE and testing; (3) peaks of anger; (4) issues around hero worship; and (5) hints of a normality. Further research exploring and documenting social media narratives around COVID-19 and the NHS, in this and subsequent lockdowns, should help in tailoring suitable support for staff in the future and acknowledging the profound impact that the pandemic has had.


2021 ◽  
Vol 9 (3) ◽  
pp. 232596712199005
Author(s):  
Jonathan S. Yu ◽  
James B. Carr ◽  
Jacob Thomas ◽  
Julianna Kostas ◽  
Zhaorui Wang ◽  
...  

Background: Social media posts regarding ulnar collateral ligament (UCL) injuries and reconstruction surgeries have increased in recent years. Purpose: To analyze posts shared on Instagram and Twitter referencing UCL injuries and reconstruction surgeries to evaluate public perception and any trends in perception over the past 3 years. Study Design: Cross-sectional study. Methods: A search of a 3-year period (August 2016 and August 2019) of public Instagram and Twitter posts was performed. We searched for >22 hashtags and search terms, including #TommyJohn, #TommyJohnSurgery, and #tornUCL. A categorical classification system was used to assess the sentiment, media format, perspective, timing, accuracy, and general content of each post. Post popularity was measured by number of likes and comments. Results: A total of 3119 Instagram posts and 267 Twitter posts were included in the analysis. Of the 3119 Instagram posts analyzed, 34% were from patients, and 28% were from providers. Of the 267 Twitter posts analyzed, 42% were from patients, and 16% were from providers. Although the majority of social media posts were of a positive sentiment, over the past 3 years, there was a major surge in negative sentiment posts (97% increase) versus positive sentiment posts (9% increase). Patients were more likely to focus their posts on rehabilitation, return to play, and activities of daily living. Providers tended to focus their posts on education, rehabilitation, and injury prevention. Patient posts declined over the past 3 years (–28%), whereas provider posts increased substantially (110%). Of posts shared by health care providers, 4% of posts contained inaccurate or misleading information. Conclusion: The majority of patients who post about their UCL injury and reconstruction on social media have a positive sentiment when discussing their procedure. However, negative sentiment posts have increased significantly over the past 3 years. Patient content revolves around rehabilitation and return to play. Although patient posts have declined over the past 3 years, provider posts have increased substantially with an emphasis on education.


Author(s):  
Irina Wedel ◽  
Michael Palk ◽  
Stefan Voß

AbstractSocial media enable companies to assess consumers’ opinions, complaints and needs. The systematic and data-driven analysis of social media to generate business value is summarized under the term Social Media Analytics which includes statistical, network-based and language-based approaches. We focus on textual data and investigate which conversation topics arise during the time of a new product introduction on Twitter and how the overall sentiment is during and after the event. The analysis via Natural Language Processing tools is conducted in two languages and four different countries, such that cultural differences in the tonality and customer needs can be identified for the product. Different methods of sentiment analysis and topic modeling are compared to identify the usability in social media and in the respective languages English and German. Furthermore, we illustrate the importance of preprocessing steps when applying these methods and identify relevant product insights.


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